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Paper Citation Record · LEDGER

Generalizable Spectral Embedding with an Application to UMAP

As of 14 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2501.11305.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.11305 v2

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:30:55.507277Z

measured 69 of 69 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

69 of 69 outbound references displayed

  • verified exact24
  • verified fuzzy8
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 34dccc92-55a6-43fc-8cd7-b40883fc264d · outbound

This paper cites an unresolved cited work.

Generalizable Spectral Embedding with an Application to UMAP Unresolved cited work

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 49a17935-b878-4e2a-b6a2-c13da2db119a · outbound

This paper cites Local graph partitioning using pagerank vectors.

Generalizable Spectral Embedding with an Application to UMAP Local graph partitioning using pagerank vectors

Reference 2

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Observation ed9f8add-0b90-4cd2-81c5-d7c2234c8f83 · outbound

This paper cites A spectral algorithm for envelope reduction of sparse matrices.

Generalizable Spectral Embedding with an Application to UMAP A spectral algorithm for envelope reduction of sparse matrices

Reference 3

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Source-reported events for the cited work

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Observation 51f791b7-da46-4b09-b942-184e71421a0b · outbound

This paper cites Directional Graph Networks.

Generalizable Spectral Embedding with an Application to UMAP Directional Graph Networks

Reference 4

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Observation db73be3c-94c7-4615-84e1-9be674e87641 · outbound

This paper cites Laplacian eigenmaps for dimensionality reduction and data representation.

Generalizable Spectral Embedding with an Application to UMAP Laplacian eigenmaps for dimensionality reduction and data representation

Reference 5

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Observation 6ba39056-e168-4f2a-9d91-94f0c6efbe41 · outbound

This paper cites Convergence of laplacian eigenmaps.

Generalizable Spectral Embedding with an Application to UMAP Convergence of laplacian eigenmaps

Reference 6

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Observation cf21d5c3-be97-4722-8b11-1a67b7061378 · outbound

This paper cites Locally optimal block preconditioned conjugate gradient method for hierarchical matrices.

Generalizable Spectral Embedding with an Application to UMAP Locally optimal block preconditioned conjugate gradient method for hierarchical matrices

Reference 7

Resolution
verified exact
doi, observed 2026-08-10T18:30:56.529952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 0fd3a49b-533e-4fab-aac5-a55f467c958e · outbound

This paper cites Algebraic multigrid (amg) for sparse matrix equations.

Generalizable Spectral Embedding with an Application to UMAP Algebraic multigrid (amg) for sparse matrix equations

Reference 8

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2d56a31a-4638-4d29-b092-24ab92b11d4d · outbound

This paper cites Dynamic graph theoretical analysis of functional connectivity in parkinson's disease: The importance of fiedler value.

Generalizable Spectral Embedding with an Application to UMAP Dynamic graph theoretical analysis of functional connectivity in parkinson's disease: The importance of fiedler value

Reference 9

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raw_fallback, observed 2026-08-10T18:30:57.449946Z

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Observation fc2243ab-8f47-478b-88e8-6826f6252414 · outbound

This paper cites Laplacian eigenmaps and principal curves for high resolution pseudotemporal ordering of single-cell rna-seq profiles.

Generalizable Spectral Embedding with an Application to UMAP Laplacian eigenmaps and principal curves for high resolution pseudotemporal ordering of single-cell rna-seq profiles

Reference 10

Resolution
verified exact
doi, observed 2026-08-10T18:30:56.507364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 628de15d-3c36-4064-884d-a4d28b8524af · outbound

This paper cites Appliances Energy Prediction.

Generalizable Spectral Embedding with an Application to UMAP Appliances Energy Prediction

Reference 11

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T18:30:55.060290Z digest=sha256:73962fb9cf07d70baa4f9f56e2fb4dc779b5f1695c5548cb90d4f424dd733335

Observation b48b8ed7-29a0-4f95-a5f3-c6812c514548 · outbound

This paper cites SpecNet2: Orthogonalization-free spectral embedding by neural networks.

Generalizable Spectral Embedding with an Application to UMAP SpecNet2: Orthogonalization-free spectral embedding by neural networks

Reference 12

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8166b359-3fa5-4c97-a7fa-7e2dc8998c1a · outbound

This paper cites Intrinsic map dynamics exploration for uncharted effective free-energy landscapes.

Generalizable Spectral Embedding with an Application to UMAP Intrinsic map dynamics exploration for uncharted effective free-energy landscapes

Reference 13

Resolution
verified exact
doi, observed 2026-08-10T18:30:56.436936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 7c987b01-5a49-483d-a298-a05045150c83 · outbound

This paper cites Deep learning for classical japanese literature, 2018.

Generalizable Spectral Embedding with an Application to UMAP Deep learning for classical japanese literature, 2018

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1a0ed3d9-654d-46f9-aff9-654d8d59dd61 · outbound

This paper cites Geometric harmonics: a novel tool for multiscale out-of-sample extension of empirical functions.

Generalizable Spectral Embedding with an Application to UMAP Geometric harmonics: a novel tool for multiscale out-of-sample extension of empirical functions

Reference 15

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Observation 31c63b76-bbe0-4a27-80f8-a5cef56d05cd · outbound

This paper cites Diffusion maps.

Generalizable Spectral Embedding with an Application to UMAP Diffusion maps

Reference 16

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no resolver link, observed 2026-08-10T18:30:55.103460Z

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Observation 537b5bab-5bb4-46d0-adcb-5a12bf079763 · outbound

This paper cites From $t$-SNE to UMAP with contrastive learning.

Generalizable Spectral Embedding with an Application to UMAP From $t$-SNE to UMAP with contrastive learning

Reference 17

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Observation eed640f9-d189-44f6-be16-b426d9bf7c8e · outbound

This paper cites Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering.

Generalizable Spectral Embedding with an Application to UMAP Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

Reference 18

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no resolver link, observed 2026-08-10T18:30:55.117730Z

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Observation 5fdf4b76-152b-435e-bc74-bcb0604b12d9 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research [best of the web].

Generalizable Spectral Embedding with an Application to UMAP The mnist database of handwritten digit images for machine learning research [best of the web]

Reference 19

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no resolver link, observed 2026-08-10T18:30:55.124430Z

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source=arxiv_source observed=2026-08-10T18:30:55.124430Z digest=sha256:348e25dd44916073ed02c8b7bf82064415ff0072fea7de1704f8434741d063c7

Observation 83d75438-867b-4c9a-a204-bdb19d685211 · outbound

This paper cites NeuralEF: Deconstructing Kernels by Deep Neural Networks.

Generalizable Spectral Embedding with an Application to UMAP NeuralEF: Deconstructing Kernels by Deep Neural Networks

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:30:56.327425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 79eb2ede-be93-4d6f-98b1-3d6bbcd2ec8c · outbound

This paper cites Compression of cerebellar functional gradients in schizophrenia.

Generalizable Spectral Embedding with an Application to UMAP Compression of cerebellar functional gradients in schizophrenia

Reference 21

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 7dc99d7e-91e1-489b-a0da-2dd62a71b03c · outbound

This paper cites Visual exploration of relationships and structure in low-dimensional embeddings.

Generalizable Spectral Embedding with an Application to UMAP Visual exploration of relationships and structure in low-dimensional embeddings

Reference 22

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no resolver link, observed 2026-08-10T18:30:55.145828Z

Source-reported events for the cited work

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Observation 129e437f-3678-45c2-ba79-93a69d660ab2 · outbound

This paper cites Algebraic connectivity of graphs.

Generalizable Spectral Embedding with an Application to UMAP Algebraic connectivity of graphs

Reference 23

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Observation 6130b749-d010-4d9d-9cb0-ae52e1c7118c · outbound

This paper cites A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory.

Generalizable Spectral Embedding with an Application to UMAP A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory

Reference 24

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metadata mismatch
raw_fallback, observed 2026-08-10T18:30:57.049105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a1fedb1e-be4c-4d28-8ebf-ef34bcae5916 · outbound

This paper cites EigenGame: PCA as a Nash Equilibrium.

Generalizable Spectral Embedding with an Application to UMAP EigenGame: PCA as a Nash Equilibrium

Reference 25

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Observation 11980361-48ad-4f34-a6b4-fdd6a1aa2769 · outbound

This paper cites Sampling a rare protein transition using quantum annealing.

Generalizable Spectral Embedding with an Application to UMAP Sampling a rare protein transition using quantum annealing

Reference 26

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Observation 9fb9e757-4283-494f-a2e1-32fd2f484b2d · outbound

This paper cites Similarity search in high dimensions via hashing.

Generalizable Spectral Embedding with an Application to UMAP Similarity search in high dimensions via hashing

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:30:57.663271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a7b7549b-abe5-4c05-ac1b-b13c37855f27 · outbound

This paper cites Unsupervised learning methods for molecular simulation data.

Generalizable Spectral Embedding with an Application to UMAP Unsupervised learning methods for molecular simulation data

Reference 28

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Observation 629fbae3-1b33-4f73-95ad-7254b4200287 · outbound

This paper cites Revealing the hidden structure of disordered materials by parameterizing their local structural manifold.

Generalizable Spectral Embedding with an Application to UMAP Revealing the hidden structure of disordered materials by parameterizing their local structural manifold

Reference 29

Resolution
verified exact
doi, observed 2026-08-10T18:30:56.222276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation c4d58c4b-8610-4ac5-8f6a-15e686ca5f36 · outbound

This paper cites Alternating diffusion maps for multimodal data fusion.

Generalizable Spectral Embedding with an Application to UMAP Alternating diffusion maps for multimodal data fusion

Reference 30

Resolution
verified exact
doi, observed 2026-08-10T18:30:56.202959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.210775Z digest=sha256:646a760c22436a5e1e696a111db73da2f69c2573b9907f8b5f21e23bfbf8c257

Observation 34e9ba18-0443-49ba-aa89-b58fe3548e20 · outbound

This paper cites Parametric t-Stochastic Neighbor Embedding With Quantum Neural Network.

Generalizable Spectral Embedding with an Application to UMAP Parametric t-Stochastic Neighbor Embedding With Quantum Neural Network

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:30:56.184673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.219557Z digest=sha256:73763b48e05b65ddf5d50352117c417c0ac35a3965634dceebef187f37cdf0ee

Observation 24f77f72-6573-48e8-b05f-335983248231 · outbound

This paper cites A survey of machine learning techniques applied to self-organizing cellular networks.

Generalizable Spectral Embedding with an Application to UMAP A survey of machine learning techniques applied to self-organizing cellular networks

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.228066Z digest=sha256:e8a5f6cc04c98f9c26ce321b7a503919f809b339263dea85c7a3eb35212df1b2

Observation 7ce7269a-8283-44ed-ad91-e3a56aefbc32 · outbound

This paper cites Initialization is critical for preserving global data structure in both t-sne and umap.

Generalizable Spectral Embedding with an Application to UMAP Initialization is critical for preserving global data structure in both t-sne and umap

Reference 33

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unresolved
no resolver link, observed 2026-08-10T18:30:55.236475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.236475Z digest=sha256:477dedc502dfb95d907c17db51e16c120e35ce8ef3b8a1c58e5e4fa2e42fc1bf

Observation 289e79b6-0414-4ae4-87c9-bd90af7521b6 · outbound

This paper cites Automatic domain decomposition of proteins by a gaussian network model.

Generalizable Spectral Embedding with an Application to UMAP Automatic domain decomposition of proteins by a gaussian network model

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-10T18:30:57.643191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.245107Z digest=sha256:e7df785396b66c15c365844285e4179f31079a192d5033252e658405f1851348

Observation 0e227d5d-648e-437b-bbf2-47765afc2cef · outbound

This paper cites Data fusion and multicue data matching by diffusion maps.

Generalizable Spectral Embedding with an Application to UMAP Data fusion and multicue data matching by diffusion maps

Reference 35

Resolution
verified exact
doi, observed 2026-08-10T18:30:56.152329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.255161Z digest=sha256:8dfa247c15a57556096d7ac3d9cb041129e65dac0c9e3c2f7e64ab790e3676f5

Observation 8edcff06-d9d7-41b3-a285-54b1f7b03b7b · outbound

This paper cites Learning the geometry of common latent variables using alternating-diffusion.

Generalizable Spectral Embedding with an Application to UMAP Learning the geometry of common latent variables using alternating-diffusion

Reference 36

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unresolved
no resolver link, observed 2026-08-10T18:30:55.265206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.265206Z digest=sha256:0e37649c9b0de2b7e2ad4687bd75ac1465105b1489e4fa6eefe093b375e95e0f

Observation 4ff229c7-2d5e-4b5c-9cba-0468cecc5a07 · outbound

This paper cites ARPACK users' guide: solution of large-scale eigenvalue problems with implicitly restarted Arnoldi methods.

Generalizable Spectral Embedding with an Application to UMAP ARPACK users' guide: solution of large-scale eigenvalue problems with implicitly restarted Arnoldi methods

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:30:57.625346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.271401Z digest=sha256:1ade3d9d39b2ca4490569f9ea1d7cb7abcde09e33dcdcb47649ad3eda27be8b8

Observation 30e88e86-1ccb-4942-b41f-209eb26fe0e3 · outbound

This paper cites Data classification methodology for electronic noses using uniform manifold approximation and projection and extreme learning machine.

Generalizable Spectral Embedding with an Application to UMAP Data classification methodology for electronic noses using uniform manifold approximation and projection and extreme learning machine

Reference 38

Resolution
verified exact
doi, observed 2026-08-10T18:30:56.114429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.280402Z digest=sha256:c7663f6139951573cf94d3cf82f8ceb656c63d3c5772ec83bf06c7e6318904c0

Observation e563726b-01b5-41e5-b513-df3097853765 · outbound

This paper cites Rayleigh quotient based optimization methods for eigenvalue problems.

Generalizable Spectral Embedding with an Application to UMAP Rayleigh quotient based optimization methods for eigenvalue problems

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.290036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.290036Z digest=sha256:81ed9e706f7b6ac7031604d21538003f02ebe4b12adc98dabf57b41722fb9ca7

Observation 7cfdf188-8284-417d-ad4c-deb144c27e28 · outbound

This paper cites Sign and Basis Invariant Networks for Spectral Graph Representation Learning.

Generalizable Spectral Embedding with an Application to UMAP Sign and Basis Invariant Networks for Spectral Graph Representation Learning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.295995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.295995Z digest=sha256:4c5ebc056db714b362710856feda56ef85a95b469f4a843a2a7565dfa4c5755f

Observation 027fce72-ad42-492b-9635-520d183aeef5 · outbound

This paper cites Umap-pytorch: Umap (uniform manifold approximation and projection) in pytorch, 2024.

Generalizable Spectral Embedding with an Application to UMAP Umap-pytorch: Umap (uniform manifold approximation and projection) in pytorch, 2024

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:30:57.601640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.302969Z digest=sha256:64108fb343218cd35f262b80fde53998f6f8358f673861d12372be5b77160bc4

Observation 3f32ef41-e965-4bcb-b8d1-a099ac6fc24b · outbound

This paper cites Banknote Authentication.

Generalizable Spectral Embedding with an Application to UMAP Banknote Authentication

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.310515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.310515Z digest=sha256:c7bc2f63b72bdddcd55d1db3b462663eb512b5f628ce881a376c21c714ba399c

Observation 6c9822e6-6212-4206-b442-1cd359ce15c4 · outbound

This paper cites Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding.

Generalizable Spectral Embedding with an Application to UMAP Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:30:56.045539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.318453Z digest=sha256:6e741c1a80c43499d2336f3bf057289cc6f458b3ef5fc8b8e8813e181fec428b

Observation f379d5eb-8d37-4091-9260-2426bf5023a6 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Generalizable Spectral Embedding with an Application to UMAP UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.326767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.326767Z digest=sha256:cfd900cbc9de5bdfde8ebf463d2a24cf96db6ca0306444929ae6fad64633deb5

Observation 10b001b1-38f6-46a0-8162-c361b9324276 · outbound

This paper cites Diffusion Nets.

Generalizable Spectral Embedding with an Application to UMAP Diffusion Nets

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:30:55.998807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.336297Z digest=sha256:5ffcc86a85afe6ac0ef3f5639471c3c2dfc161d409771394b675639f467f340c

Observation 83b8d14f-46a3-4701-b8c5-6d81075a4ec8 · outbound

This paper cites o m. \"U ber die praktische aufl \.

Generalizable Spectral Embedding with an Application to UMAP o m. \"U ber die praktische aufl \

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.348032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.348032Z digest=sha256:63d7b23fd0cb69af101d4dcbd047b85630e5b47f59557e11bf4a67e644e781ec

Observation b9a76f7d-7511-4845-88fb-7b292180efa9 · outbound

This paper cites Graph signal processing: Overview, challenges, and applications.

Generalizable Spectral Embedding with an Application to UMAP Graph signal processing: Overview, challenges, and applications

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.355969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.355969Z digest=sha256:252d48e24394416e0802c98c7377e4a429ec22603183f86371a26f10baff3226

Observation f53f642d-bf35-4274-a863-de0d484959a4 · outbound

This paper cites Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism.

Generalizable Spectral Embedding with an Application to UMAP Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism

Reference 48

Resolution
verified exact
doi, observed 2026-08-10T18:30:55.955667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.361772Z digest=sha256:2d3487bb0037e8d641b62a96ea9b495c621f41183cf0c23553897ebf7afeddc1

Observation 29283fd9-4260-4d5f-954d-4a4509160a4e · outbound

This paper cites Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology.

Generalizable Spectral Embedding with an Application to UMAP Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology

Reference 49

Resolution
verified exact
doi, observed 2026-08-10T18:30:55.932734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.367319Z digest=sha256:b72e5be73c750ebb88492d196ace1378959201833be8b79d89878f6184c9db7e

Observation d8d51069-6b50-4196-b5af-04e72bccedc5 · outbound

This paper cites Spectral Inference Networks: Unifying Deep and Spectral Learning.

Generalizable Spectral Embedding with an Application to UMAP Spectral Inference Networks: Unifying Deep and Spectral Learning

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.372481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.372481Z digest=sha256:77ff70df258a8a3d4eaba7835b8450732d60a5158e148cbdef3b6f79632c5397

Observation 2a19b8c6-5376-4a8f-8987-a48c3ea43130 · outbound

This paper cites Parametric UMAP embeddings for representation and semi-supervised learning.

Generalizable Spectral Embedding with an Application to UMAP Parametric UMAP embeddings for representation and semi-supervised learning

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.381094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.381094Z digest=sha256:2a07bf0ecdce75b8ca78b2756b43bbb377daa79f9a5e1c7bfc92dce7606fb906

Observation 0e712f0a-b1c5-46eb-b595-bd69b12d61d1 · outbound

This paper cites Using genetic programming to find functional mappings for umap embeddings.

Generalizable Spectral Embedding with an Application to UMAP Using genetic programming to find functional mappings for umap embeddings

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.391229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.391229Z digest=sha256:bfee1c753bf88f4e2b2d742972754637518c8f4f8b2fa111d73534c949599df9

Observation 4505d461-fa93-435d-ba5f-dd6836497468 · outbound

This paper cites SpectralNet: Spectral Clustering using Deep Neural Networks.

Generalizable Spectral Embedding with an Application to UMAP SpectralNet: Spectral Clustering using Deep Neural Networks

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.398445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.398445Z digest=sha256:d21d62aad1afd3b320074fd81a2810c55fc59ab67bf96b372e43a41f600f8d14

Observation 2eab494c-bdfa-4829-97d1-86195749d072 · outbound

This paper cites Amino acid partitioning using a fiedler vector model.

Generalizable Spectral Embedding with an Application to UMAP Amino acid partitioning using a fiedler vector model

Reference 54

Resolution
verified exact
doi, observed 2026-08-10T18:30:55.840047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.404724Z digest=sha256:21ab8146c21ee57f07bf4fb38dbd6bf666d286920346f5b3dbb238851ed041bf

Observation 2f142084-248c-4a91-bf7e-d9b125b87456 · outbound

This paper cites Convergence of Laplacian spectra from random samples.

Generalizable Spectral Embedding with an Application to UMAP Convergence of Laplacian spectra from random samples

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:30:55.817622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.411882Z digest=sha256:8e3b70efce976a6d9c6d5a1ad856a95d655610aa347df578d2e93cee6f30f0ff

Observation bd2b3825-f968-4b84-a02d-849dcddf7249 · outbound

This paper cites BASiS: Batch Aligned Spectral Embedding Space.

Generalizable Spectral Embedding with an Application to UMAP BASiS: Batch Aligned Spectral Embedding Space

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:30:55.781246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.417376Z digest=sha256:e4bad5ecbe74f1a7677efa7d9316699ce9248d3f9af76e6004e35c986efe829d

Observation a1952cc4-74c7-4a1e-8a76-6d6562d51d5d · outbound

This paper cites Fiedler Regularization: Learning Neural Networks with Graph Sparsity.

Generalizable Spectral Embedding with an Application to UMAP Fiedler Regularization: Learning Neural Networks with Graph Sparsity

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.427309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.427309Z digest=sha256:867de05c79809468dc98fdb84d53179d89b01241b27be65042bc9e8dd0846aac

Observation b2feb6f5-348d-4e99-adde-20e3b9783c01 · outbound

This paper cites Parkinsons Telemonitoring.

Generalizable Spectral Embedding with an Application to UMAP Parkinsons Telemonitoring

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.433520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.433520Z digest=sha256:59a484887bfa144e710a345be457fb55f4f7839abf670a1b02966bd23b6d691a

Observation c963a5e9-dcc8-40ba-895f-f72ad779df9b · outbound

This paper cites Learning a parametric embedding by preserving local structure.

Generalizable Spectral Embedding with an Application to UMAP Learning a parametric embedding by preserving local structure

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:30:57.582448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.440791Z digest=sha256:ebc6478a894cd3e2d23ce9b49795ba189f8236aa1a70dc34968069caa7e9bdda

Observation 1a4893c2-5d04-4a94-b607-4236883c0a47 · outbound

This paper cites A Tutorial on Spectral Clustering.

Generalizable Spectral Embedding with an Application to UMAP A Tutorial on Spectral Clustering

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.446711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.446711Z digest=sha256:d26a91f1234b718971b025d4843c11a2ce35729f3ee0cbeda60edd246cb02951

Observation ca1abfed-a899-45bd-9c34-509f16f15c8e · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Generalizable Spectral Embedding with an Application to UMAP Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.457071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.457071Z digest=sha256:519e10b649f0256dfaa8327970613f306f5a25cd1c0010360d4857d90027b8d2

Observation 42307207-a5f7-48c5-b2c9-c30ffa011398 · outbound

This paper cites Integrative multiscale biochemical mapping of the brain via deep-learning-enhanced high-throughput mass spectrometry.

Generalizable Spectral Embedding with an Application to UMAP Integrative multiscale biochemical mapping of the brain via deep-learning-enhanced high-throughput mass spectrometry

Reference 62

Resolution
verified exact
doi, observed 2026-08-10T18:30:55.677368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.464038Z digest=sha256:d22baa047bfd94028d6655b89f968522eaab2bfc8437dc214a21514d36cde403

Observation ba74b745-8aa7-4c49-92bf-2dd3fd27f657 · outbound

This paper cites Robust parametric umap for the analysis of single-cell data.

Generalizable Spectral Embedding with an Application to UMAP Robust parametric umap for the analysis of single-cell data

Reference 63

Resolution
verified exact
doi, observed 2026-08-10T18:30:55.657871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.470341Z digest=sha256:eb2323c76bd7d01f39ba2eb0a67bd2a7b0738d78a3904f0199485d06c5d81604

Observation d80c0878-914b-4852-8209-934d03ae07d3 · outbound

This paper cites Online learning of open-set speaker identification by active user-registration.

Generalizable Spectral Embedding with an Application to UMAP Online learning of open-set speaker identification by active user-registration

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:30:57.565766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.478902Z digest=sha256:3a3f5c84964437c6d60ee31777500333ddf239a731edaa173efd0e2eec4bf6a5

Observation ed8fed63-9d50-43a1-b1a9-e274d3333dfe · outbound

This paper cites Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs.

Generalizable Spectral Embedding with an Application to UMAP Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs

Reference 65

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:30:55.637145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.484849Z digest=sha256:1f3f1ea407e0d4132529a317796f984f05146e6266ef01c0cf89140ffe94d588

Observation 7c2f07fa-ec1b-4a2c-9ac1-073f2585fa65 · outbound

This paper cites Delineation of folding pathways of a -sheet miniprotein.

Generalizable Spectral Embedding with an Application to UMAP Delineation of folding pathways of a -sheet miniprotein

Reference 66

Resolution
verified exact
doi, observed 2026-08-10T18:30:55.604325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.490258Z digest=sha256:acdee154332e35a19a98db09c3c8d78245d07e45e21af057858f795f9b2aeee4

Observation 4efc062f-a633-4558-b03a-0c5e74104a74 · outbound

This paper cites Rapid exploration of configuration space with diffusion-map-directed molecular dynamics.

Generalizable Spectral Embedding with an Application to UMAP Rapid exploration of configuration space with diffusion-map-directed molecular dynamics

Reference 67

Resolution
verified exact
doi, observed 2026-08-10T18:30:55.585766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.495390Z digest=sha256:4d4e3c9e9a7deec46243fbf462b52b472865d7ea4ea0e9d48edbc54eb2b552fe

Observation 2bde2e7a-941b-4c59-92d8-5ad9bd43df9a · outbound

This paper cites A fiedler vector scoring approach for novel rna motif selection.

Generalizable Spectral Embedding with an Application to UMAP A fiedler vector scoring approach for novel rna motif selection

Reference 68

Resolution
verified exact
doi, observed 2026-08-10T18:30:55.564635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T18:30:55.501757Z digest=sha256:b0b26655b2326864b7bd6ef02ec63f0addcc774d6fa9fe19842f8b33fa6647cb

Observation 9a83ce5c-ca31-475c-9ad0-49c9bd63babe · outbound

This paper cites write newline.

Generalizable Spectral Embedding with an Application to UMAP write newline

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-10T18:30:55.507277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T18:30:55.507277Z digest=sha256:2a254b7a90dad25eb4a2a0b14077a81af439a50166d0988aadd9989f385876bd

Pith citing papers

No inbound Pith citation observations are available.