Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-08T04:41:05.376170Z
Paper Citation Record · LEDGER
As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.06497.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-08T04:41:05.376170Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
34 of 34 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation b00800dd-1f99-479c-80e0-6b5149344363 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Schwartz
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 01473e3e-1649-4092-b999-396430ef3686 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Development 146(12), 173849 (2019) https://doi.org/10.1242/dev.173849
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a0c1b016-0b58-4223-bb78-f6f631254180 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Belkin and P
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4da7251e-01da-4f8b-a410-5cc79a731a36 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Convergence of laplacian eigenmaps
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 99540453-36ac-4779-bddb-7f525f34ada0 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Graph approximations to geodesics on embedded manifolds
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 71d1f989-fc88-4686-9eca-fa4e8f43d063 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning M., WACLAW, B
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b4af4985-e0c3-4541-ab7d-0a33827ea9d4 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Coifman and Stéphane Lafon
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 79d6124c-f7e7-4b98-8a59-6ee8468b6619 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Stability of graph communities across time scales
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 005cd868-7294-424b-bff0-6f56953abec0 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Donoho and Carrie Grimes
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 01113dd5-bf23-4e84-8765-9a65f3626af2 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Statistical-mechanical approach to subgraph centrality in complex networks.Chemical Physics Letters, 439(1):247–251, 2007
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1713f1c6-dbb1-406e-b655-861897184994 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Nature Methods13(10), 845–848 (2016) https://doi.org/10.1038/nmeth.3971
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0ef7fa08-ed5d-4ade-8a94-30adf88c8246 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Graph laplacians and their convergence on random neighborhood graphs.J
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 61afbc2e-ff98-479c-9e2a-b59b9aac5c6b · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning A heat diffusion perspective on geodesic preserving dimensionality reduction
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9ed04b5d-22e5-4474-b8dd-7a5e154c355d · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Kastriti, Peter Lonnerberg, Alessandro Furlan, Jean Fan, Lars E
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c848887b-007c-42be-bfc9-05ed78b78bd4 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Coupling from the past
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8676cea3-3b66-43ed-8ec4-e5565efc2351 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Path integral based convolution and pooling for graph neural networks
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ff29c553-909d-4ea7-8cfb-717425e04e64 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9c7d756a-b211-49f7-8ee2-214acf5156ec · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Visualizing structure and transitions in high-dimensional biological data
Reference 18
Source-reported events for the cited work
correction dated 2020-01-02. Source: crossref record 10.1038/s41587-019-0395-5->10.1038/s41587-019-0336-3:correction, observed 2026-07-11T03:09:44.372789+00:00. This notice travels one citation hop only.
Observation 4961e707-ac9d-49d3-8c6d-96a1d900faf8 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning A note on a method for generating points uniformly on n-dimensional spheres
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8a394168-876c-4fee-8225-05c92638cdd8 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Hamey, Blanca Pijuan Sala, Evangelia Diamanti, Mairi Shepherd, Elisa Laurenti, Nicola K
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 40828f7e-ad88-4a66-b0c4-8f8bc09d99d0 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Unresolved cited work
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 82055c3e-78b8-4962-a2dd-aaf2ee28e57a · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Transcriptional heterogeneity and lineage commitment in myeloid progenitors.Cell, 163(7):1663–1677, 2015
Reference 22
Source-reported events for the cited work
correction dated 2016-01-15. Source: crossref record 10.1016/j.cell.2015.12.046->10.1016/j.cell.2015.11.013:correction, observed 2026-07-11T03:18:00.181309+00:00. This notice travels one citation hop only.
Observation 800cbba6-c021-4249-b667-4cd01fba399a · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Science , volume=
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8c9ce12f-11a3-4f44-9d00-a8e229e4ae47 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Satpathy, Jeffrey M
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 64de3c3a-056c-47e6-a273-84e5e5e70d10 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Nolan, Benjamin J
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 6498caf5-1094-402a-9d9a-682f40761bc7 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Global versus local methods in nonlinear dimensionality reduction
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation bc783d7c-0cae-439b-8be0-d15aabcbd7b6 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Tenenbaum, Vin de Silva, and John C
Reference 27
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8e194539-2597-4b75-844f-2652112fe63d · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Trapnell, D
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 501e5e79-2244-401d-9931-f989fb224ea3 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Visualizing data using t-sne.Journal of Machine Learning Research, 9(86):2579–2605, 2008
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fb8d016b-186a-4252-a8fd-b2e680936a0e · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Unresolved cited work
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7fa85c78-f973-4d98-a1ba-fb1ade00f9da · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Venna and S
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2bcfd4a1-3024-4f2a-a9fc-7eebda4b9797 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Diffusive topology preserving manifold distances for single-cell data analysis.Proceedings of the National Academy of Sciences, 122 (4):e2404860121, 2025
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 45e62e75-135f-4ee6-8538-28c5b47cfae2 · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Alexander Wolf, Philipp Angerer, and Fabian J
Reference 33
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 557714a3-e560-40fc-b6e7-1e335a93d26a · outbound
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning Self-tuning spectral clustering
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
No inbound Pith citation observations are available.