{"as_of":"2026-08-16T04:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3fde7b7e317cd68aea2bb17e0be70d9ba02c12a8aa32771e47eb4e5a04826511","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:09:59.969053Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-24T16:06:15.543657Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1903.05858","last_updated":"2019-11-03T00:26:43Z","snapshot_observed_at":"2026-08-16T00:41:30.717734Z","submitted_at":"2019-03-14T08:45:13Z","title":"Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.05858","snapshot_observed_at":"2026-08-14T14:09:59.969053Z","title":"Better Approximations of High Di- mensional Smooth Functions by Deep Neural Networks with Rectiﬁe d Power Units","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.03833","last_updated":"2019-08-11T00:40:43Z","snapshot_observed_at":"2026-08-15T03:21:22.751656Z","submitted_at":"2019-08-11T00:40:43Z","title":"Space-time error estimates for deep neural network approximations for differential equations","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T14:09:59.969053Z"},"links":{"cited_paper":"/paper/1903.05858","citing_paper":"/paper/1908.03833"},"observation_digest":"sha256:09666f69b00a497278d3bed730b63e3358c17feef7a307549d4f78f23057d45a","observation_id":"4669c1f1-3330-49d9-90c2-4fc8cc3b38f3","resolution":{"observed_at":"2026-08-14T14:09:59.969053Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.05858","last_updated":"2019-11-03T00:26:43Z","snapshot_observed_at":"2026-08-16T00:41:30.717734Z","submitted_at":"2019-03-14T08:45:13Z","title":"Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units","version":4},"cited_work":{"arxiv_id":"1903.05858","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1903.05858","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Better approximations of high dimensional smooth functions by deep neural networks with rectiﬁed power units","venue":null,"work_id":"1a8e6b66-d589-4341-b334-ac17dbeb61d7","year":2019},"citing_paper":{"arxiv_id":"1911.05467","last_updated":"2023-12-01T08:37:27Z","snapshot_observed_at":"2026-08-13T23:29:49.354750Z","submitted_at":"2019-11-07T06:30:47Z","title":"ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units via Chebyshev Approximations","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-24T16:04:41.672358Z"},"links":{"cited_paper":"/paper/1903.05858","citing_paper":"/paper/1911.05467"},"observation_digest":"sha256:7b97dc85efb3e7e90f2adc865dde4baa1f41a7116fac13b61f866c47a9921427","observation_id":"12d8aba0-e166-486d-bfff-5442b23854b8","resolution":{"observed_at":"2026-05-24T16:06:15.547153Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.05858","last_updated":"2019-11-03T00:26:43Z","snapshot_observed_at":"2026-08-16T00:41:30.717734Z","submitted_at":"2019-03-14T08:45:13Z","title":"Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units","version":4},"cited_work":{"arxiv_id":"1903.05858","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1903.05858","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Better approximations of high dimensional smooth functions by deep neural networks with rectiﬁed power units","venue":null,"work_id":"1a8e6b66-d589-4341-b334-ac17dbeb61d7","year":2019},"citing_paper":{"arxiv_id":"2604.18143","last_updated":"2026-04-24T06:58:50Z","snapshot_observed_at":"2026-08-14T15:02:39.379856Z","submitted_at":"2026-04-20T12:07:33Z","title":"Distributional Off-Policy Evaluation with Deep Quantile Process Regression","version":2},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-05-10T04:10:14.476158Z"},"links":{"cited_paper":"/paper/1903.05858","citing_paper":"/paper/2604.18143"},"observation_digest":"sha256:d8f64642bcfd5b30dfdeab78d220ba3abf07be573cff71b05eaf79c3f8a276d9","observation_id":"3dbab6ee-b973-4243-bb1c-10ffb4bb8985","resolution":{"observed_at":"2026-05-11T12:06:03.946503Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1903.05858/citation-record","integrity":"/paper/1903.05858/integrity","json":"/paper/1903.05858/citation-record.json","paper":"/paper/1903.05858"},"outbound":[],"paper":{"arxiv_id":"1903.05858","last_updated":"2019-11-03T00:26:43Z","latest_version":4,"primary_category":"math.NA","snapshot_observed_at":"2026-08-16T00:41:30.717734Z","submitted_at":"2019-03-14T08:45:13Z","title":"Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1903.05858."}