{"as_of":"2026-08-10T20:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7c956b10bb2c97d1e219d7510e010c3efd049ebaea148f97452cc302763dc889","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-29T01:18:46.622883Z","state":"measured"},{"denominator":44,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":44,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2606.27455/citation-record","integrity":"/paper/2606.27455/integrity","json":"/paper/2606.27455/citation-record.json","paper":"/paper/2606.27455"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Directed network topology inference via graph filter identification,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:87c781404890efe5a2639f9f808c5f110a85cc7c48de955aa414dd413b388ac0","observation_id":"092f01aa-3d0e-4cb7-a874-789ef2c977ef","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Graph signal processing: Overview, challenges, and ap- plications,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:d73d17bd0a05001b94ff7ec7c75ef4eb2e7965d9f8a5356b4713e966b22208fc","observation_id":"c662ce61-56e2-477f-9292-dc7c8154f5c1","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Graphs, convolutions, and neural networks: From graph filters to graph neural networks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:3d765bcd80b97e5b619b4ffe3d8a37a1552dbb6dab757bf381c396eb317e55f4","observation_id":"00aae48e-e603-4a18-a209-66f66999111f","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Discrete signal processing on graphs,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:9487cbf21021c221c89a94e9f5fd549c642bcd5d7c21cfb8f4fc2c7eb6a310de","observation_id":"520af26c-4ea8-4b46-a082-c8361a875e32","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Signal processing on directed graphs,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:ccde5323092c7b582b6636d0d7d3cc100292fff2084c43dded629d846b0c398f","observation_id":"f8b63d0d-359c-40ea-aad6-1a6cc84b288d","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Peters, D","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:0e6b1986f2ff97f83ac7d16694f3ecebacb25a1e359619651beaa637331fc534","observation_id":"d087194f-9e58-4867-b6f6-40d303350e5e","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Stationary graph processes and spectral estimation,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:0985f5309d24488fa1bea45f3dbe8d62600aa5f79060ee7ab54778f00480ad97","observation_id":"4ac49bcd-189c-45b0-952a-128edf4c3009","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Identifying the topology of undirected networks from diffused non-stationary graph signals,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:a2ae7ac227a94d5f81f08af0a8f6c00138dc7b15c4c0c82308cdf8e6fda7aead","observation_id":"aceb238b-9dc6-4bc9-8d43-c28ca52a7f40","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Boumal,An Introduction to Optimization on Smooth Manifolds","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:384ca39718740f134dc705307f618913d3adbc3685c584d27a866feaaf98fba2","observation_id":"2a18127d-5f5e-46ef-a879-bac93a56d28d","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Topology identi- fication and learning over graphs: Accounting for nonlinearities and dynamics,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:ca950c1f4b5e28e1589192f1db74de3235bff86dc4669fab03405cfc91ef5b9e","observation_id":"8280b2c0-9613-4f00-a0d8-8fac313eefad","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Connecting the dots: Identifying network structure via graph signal processing,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:c55d3d2050e0a07a1e47b560ac89593b25b96a05d3dc30594305aae5ff7e11e0","observation_id":"8460b943-dcab-4228-96db-29bf9a61ff9d","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Disentangling neurodegeneration with brain age gap prediction models: A graph signal processing perspective,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:a3209addbce34a027556e966b984920ac848f9b4b81187101c5d6fddd9011961","observation_id":"6e906aaf-c488-4c4c-9efd-61767c50278a","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:c4065fb910af458cf123e3b70bacdf67eaa2a3b7ea3bae09a8370614bea990b0","observation_id":"b4a4db87-061d-4058-b155-a65246fae9fe","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Sparse inverse covariance estimation with the graphical lasso,","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:0ec6d871556a7a555d2dabec2511cdae5c4d7d3cdf5f86cc9497bae5d27773a5","observation_id":"31758768-5ae0-4213-92b5-a328a71672cc","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Proximal-gradient algorithms for tracking cascades over social networks,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:2b08dd31c20990343cb4240c1655dbe2ec69b123a84f0b05de8fd9cf1ce13cac","observation_id":"b6929ddc-7e23-4f1e-be00-69b92e74b5de","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Tensor decompositions for identifying directed graph topologies and tracking dynamic networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:d268a3efe5f1a0d2022ad5946f20ba09d471326669d7cc018780baa315eee4f6","observation_id":"cb2bfc11-a53f-41de-83aa-6fcd13ed96e2","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Topology identification of directed graphs via joint diagonalization of correlation matrices,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:09f8fd6e32988a406faf65b2ad59bc87c320bb68b7e18f2f3ae4cb86919d45aa","observation_id":"f92d40bc-b5d8-4790-b23b-0fad261f9fad","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2601.15999","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-01T18:55:59.340191Z","title":"A covariance matching approach to graph topology identification,","venue":null,"work_id":"723cb75e-7dd1-47eb-89d7-7febc741e6e4","year":2026},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:99cae8494ce3df56c22587f87da49ca2fc0933d356e6390f186deb2958f55baf","observation_id":"f041946b-cf72-46a8-af6b-9b80d735d5fe","resolution":{"observed_at":"2026-07-01T18:55:59.341690Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"DAGs with NO TEARS: Continuous optimization for structure learning,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:45d0d29556a2eda41b69e555fecbdc0e599379cea1eb6978cb4eeb95a7f29611","observation_id":"3a18a1c9-0929-4b29-bb09-cff4a7fa4cd2","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"CoLiDE: Concomitant linear DAG estimation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:3da91130b41f90a31c093d2add56d2015a211460240392f80331368aabc22922","observation_id":"d74fa74f-a200-4644-a3e8-32d5d63756cd","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Beta oscillations in a large-scale sensorimotor cortical net- work: Directional influences revealed by Granger causality,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:2216941a6e4fccb805cd8644e0d12862f7dbf69b71982d355075c746f604ca0d","observation_id":"849fea85-6039-4bac-a9cf-cc57c1db82cb","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Learning Laplacian matrix in smooth graph signal representations,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:a980baa9153339c8fc73af9ad4a0eac21726e189ddfadc4347928f9780f9285e","observation_id":"b32e4ddd-95ab-40bf-bab2-3a9b8deb5e27","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Signal processing on graphs: Causal modeling of unstructured data,","venue":null,"work_id":null,"year":2077},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:69b11e679aac8b0677c4702b480271d02a691839b2728c27b94c98bc7942b806","observation_id":"7581735d-852b-43f9-be37-37b1a905b9d8","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"How to learn a graph from smooth signals,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:5a8c5bc9adb1f8ef2754f37100c5786c09d25c92c08667f7b007526098826ec7","observation_id":"84134b7a-c22f-4b48-81a6-7b2cb428aa45","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Network topology inference from spectral templates,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:599fe829cbd9e2f34523f8c9f574463a64a96af2089ae4505529f7da01bc529d","observation_id":"99ed1628-16ce-438d-8e88-d959dda4f679","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Characterization and inference of graph diffusion processes from ob- servations of stationary signals,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:7235640d775c89175e3eddcb81631e5c9c7362c4175705bc7836875b8109d75a","observation_id":"15cd413d-40da-4580-ac74-811afd251743","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Learning heat diffusion graphs,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:078f18378a906d66971c96850401d7e6b4eb1308956b75e1b5bc6923a6a688a2","observation_id":"c48f432b-7b9e-421f-802d-5947bd6a7d62","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Learning graphs from data: A signal representation perspective,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:19ad78e66a6677f038572a0323eccec432e094bc1dac7954c211eaa2818fcf04","observation_id":"410e6e0d-1aaa-4572-a6c9-bc9bc8b3a31d","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Learning graphs from smooth and graph-stationary signals with hidden variables,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:e7b963c9233bc98c7c2d0c56a4a99df3d97d57a10ace83c4dafd6e005cc0b84d","observation_id":"fa957ca9-8ef0-41b3-9202-a3b8da4e9b2f","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Online discriminative graph learning from multi-class smooth signals,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:29522860bb6db61d729f61c19fc0ea7e94b46831ca7162052a9bc07e08a28b0c","observation_id":"cca80c7f-2235-4fa3-9495-603b03d2d200","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Accelerated graph learning from smooth signals,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:6e4485d0ebc2ad54730dd5216b93bbbe564584e347ef61259bbe259e65600b20","observation_id":"f43e79cb-978a-4b5d-bf20-caa69a520808","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Inferring directed network topologies via tensor factorization,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:d9f9dc1eaa690a11549a90189bedec2164f81bcecbdbcbe6f9e18f45e8ec23fb","observation_id":"229f22d8-f7fb-457a-acc1-762ed8993108","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Network topology inference from non-stationary graph signals,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:78c229674ec16b6b1b2386cbe261f1404d57af441f82625d4b41de23a8c04689","observation_id":"1372ae08-ec5c-4633-a124-05ab039a850f","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14744","last_updated":"2023-10-12T04:37:56Z","snapshot_observed_at":"2026-07-06T15:32:14.701994Z","submitted_at":"2023-05-24T05:32:49Z","title":"Block Coordinate Descent on Smooth Manifolds: Convergence Theory and Twenty-One Examples","version":3},"cited_work":{"arxiv_id":"2305.14744","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.14744","snapshot_observed_at":"2026-07-01T18:55:59.342809Z","title":"Block coordinate descent on smooth mani- folds: Convergence theory and twenty-one examples,","venue":null,"work_id":"f9590816-3dad-4ee8-8415-2906ff672c82","year":2023},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"cited_paper":"/paper/2305.14744","citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:52d94c9c4b6ce030980cee863c8370a9eb10366cf4e773722e0f6547d0b8a27e","observation_id":"f93d7d42-c137-4af9-9ede-3250fcb2a834","resolution":{"observed_at":"2026-07-01T18:55:59.344350Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Robust graph filter identification and graph denoising from signal observations,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:9361b472d87f1a4c257e27ce0eefd474b0e9c9a0b5d7168c0d575424894058f9","observation_id":"8a4bf73a-0dfd-429b-a7e1-0c826c6ce9b6","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Online topology inference from streaming stationary graph signals with partial connectivity information,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:24609b0564d5b1cd5f61c18a67da4c26acf15950ace6aae27df2b5f5184be41b","observation_id":"3f608e96-4401-4db8-bd92-097361601894","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Joint inference of multiple graphs from matrix polynomials,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:8ebe6df7e2e6613871ae9f2203d6dfbbfa0fd91d294355b3f0f11d84fb5df191","observation_id":"78d1d863-4f1c-4ceb-b2d1-4717035c19b8","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Logspect: Feasible graph learning model from stationary signals with recovery guarantees,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:38ab00afe2db1bcaf8bf8cd20ec891513819b848ee1003566477b80bfe8faf9b","observation_id":"c365aaec-d984-4b74-8e1c-055d2376aed7","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1101.6081","last_updated":"2011-02-10T02:53:50Z","snapshot_observed_at":"2026-07-06T02:22:49.108398Z","submitted_at":"2011-01-31T20:59:45Z","title":"Projection Onto A Simplex","version":2},"cited_work":{"arxiv_id":"1101.6081","doi":null,"metadata_source":"pith","pith_arxiv_id":"1101.6081","snapshot_observed_at":"2026-07-03T13:18:12.216310Z","title":"Projection Onto A Simplex","venue":"math.OC","work_id":"7d471094-9159-47c9-970b-1e1ae9a57900","year":2011},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"cited_paper":"/paper/1101.6081","citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:c2d643f355c9b46d224e7de772acc11d54f7f56b9eedf20e6aaa78fcc81daf70","observation_id":"de1931f8-beb3-464e-b265-29fb5875866b","resolution":{"observed_at":"2026-07-01T18:55:59.342925Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:30e75a27cd31ca422bd56ede94f88045bba5ffd7ae62a8544751a749271fbc90","observation_id":"5809d8e0-82ad-4e24-961a-6850f3ecd738","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Proximal alternating linearized minimization for nonconvex and nonsmooth problems,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:adbe1afff181638066ea108bf8cd2289298e433aed2acf27bcff932f78b19ac8","observation_id":"42606544-2c1e-4ec4-bbe6-bc85c65de4ef","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"On Kruskal’s uniqueness condi- tion for the CAMDECOMP/PARAFAC decomposition,","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:8e4460414ed372837e6e2d5b2d9dbbf2ead1e04a19480a7b426badb1764f108f","observation_id":"7089054c-aabc-4364-9c5b-dd3ddce6127f","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Global rates of convergence for nonconvex optimization on manifolds,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:7062d5b9dbfcd67e850f119fc55d2cd0f9fd00b79560b0bf941d82b8c7c46103","observation_id":"7a6c3580-480b-4f06-8b2b-6209d8cb0089","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T01:18:46.622883Z","title":"Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-29T01:18:46.622883Z"},"links":{"citing_paper":"/paper/2606.27455"},"observation_digest":"sha256:dcd5a9e09f101583aea60828938b11fc67bf999e33a5dc295817ecbb73cc1809","observation_id":"ad6dabb0-4c7c-4e96-a1b9-bb5e54b06abc","resolution":{"observed_at":"2026-06-29T01:18:46.622883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.27455","last_updated":"2026-06-25T18:25:57Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-10T08:42:36.298153Z","submitted_at":"2026-06-25T18:25:57Z","title":"Directed Graph Topology Inference via Graph Filter Identification"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":41,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":44},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2606.27455."}