Generalizable Spectral Embedding with an Application to UMAP | Paper Citation Record

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This paper cites an unresolved cited work.

Generalizable Spectral Embedding with an Application to UMAP Unresolved cited work

Reference 1

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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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This paper cites Directional Graph Networks.

Generalizable Spectral Embedding with an Application to UMAP Directional Graph Networks

Reference 4

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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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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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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

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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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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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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

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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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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

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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

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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

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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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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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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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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

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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

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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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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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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

Resolution: unresolved; no resolver link, observed 2026-08-10T18:30:55.179587Z

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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

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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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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

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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

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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

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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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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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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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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

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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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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

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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

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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

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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

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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

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

This paper cites Banknote Authentication.

Generalizable Spectral Embedding with an Application to UMAP Banknote Authentication

Reference 42

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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

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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

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This paper cites Diffusion Nets.

Generalizable Spectral Embedding with an Application to UMAP Diffusion Nets

Reference 45

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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.

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 2026-08-18T06:34:40.430872+00:00.

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.

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.

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 2026-08-18T06:34:40.430872+00:00.

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 2026-08-18T06:34:40.430872+00:00.

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 2026-08-18T06:34:40.430872+00:00.

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 2026-08-18T06:34:40.430872+00:00.

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 2026-08-18T06:34:40.430872+00:00.

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 2026-08-18T06:34:40.430872+00:00.

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 2026-08-18T06:34:40.430872+00:00.

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.

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