Paper Citation Record · LEDGER

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs

As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.01596.

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

pith.paper-citation-record.v1
2506.01596 v1

Coverage vector

measured 44 of 44 reference resolution

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

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External citation measurements

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Outbound references

Observation bf580fa5-3b06-4c6a-a42e-aaee7289f541 · outbound

This paper cites In: Proceedings of the Thirtieth International Joint Conference on Artifical Intelligence (IJCAI) (2021).

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: Proceedings of the Thirtieth International Joint Conference on Artifical Intelligence (IJCAI) (2021)

Reference 1

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This paper cites Neural Comput.15(6), 1373–1396 (Jun 2003).

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Neural Comput.15(6), 1373–1396 (Jun 2003)

Reference 2

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This paper cites In: In- ternational Conference on Learning Representations (2021),https://openreview.

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: In- ternational Conference on Learning Representations (2021),https://openreview

Reference 4

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This paper cites Journal of Machine Learning Research24(43), 1–48 (2023).

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Journal of Machine Learning Research24(43), 1–48 (2023)

Reference 5

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This paper cites In: Proceedings of the 40th International Conference on Machine Learning.

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: Proceedings of the 40th International Conference on Machine Learning

Reference 6

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This paper cites In: 2023 IEEE Ninth Multimedia Big Data (BigMM).

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: 2023 IEEE Ninth Multimedia Big Data (BigMM)

Reference 7

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This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Fast Graph Representation Learning with PyTorch Geometric

Reference 8

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This paper cites Advances in Neural Information Processing Systems 36, 2056–2073 (2023).

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Advances in Neural Information Processing Systems 36, 2056–2073 (2023)

Reference 11

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This paper cites In: The Third Learning on Graphs Conference (2024),https://openreview.net/forum? id=ZKHV6Cpsxg.

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: The Third Learning on Graphs Conference (2024),https://openreview.net/forum? id=ZKHV6Cpsxg

Reference 12

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Reference 13

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This paper cites In: The Thirty-eighth Annual Con- ference on Neural Information Processing Systems (2024),https://openreview.

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: The Thirty-eighth Annual Con- ference on Neural Information Processing Systems (2024),https://openreview

Reference 14

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This paper cites Recent implementations, applications, and extensions of the Locally Optimal Block Preconditioned Conjugate Gradient method (LOBPCG).

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Recent implementations, applications, and extensions of the Locally Optimal Block Preconditioned Conjugate Gradient method (LOBPCG)

Reference 16

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This paper cites KDD2019, 1269–1278 (Aug 2019).

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs KDD2019, 1269–1278 (Aug 2019)

Reference 17

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This paper cites In: The Eleventh International Conference on Learning Representations (2023), https: //openreview.net/forum?id=Q-UHqMorzil.

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: The Eleventh International Conference on Learning Representations (2023), https: //openreview.net/forum?id=Q-UHqMorzil

Reference 20

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This paper cites In: Science of Cyber Security, pp.

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: Science of Cyber Security, pp

Reference 21

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This paper cites In: NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations (2022),https: //openreview.net/forum?id=BNhhZwAlVNC.

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations (2022),https: //openreview.net/forum?id=BNhhZwAlVNC

Reference 22

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Transactions on Machine Learning Research (2024), https: //openreview.net/forum?id=BTgHh0gSSc

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: Proceedings of the AAAI conference on artificial intelli- gence

Reference 24

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs PyTorch: An Imperative Style, High-Performance Deep Learning Library

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Advances in Neural Infor- mation Processing Systems35 (2022)

Reference 27

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: ICML 2020 Work- shop on Graph Representation Learning (2020) 16 Y

Reference 28

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs arXiv [physics.soc-ph] (Sep 2019)

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs net/forum?id=S19eAF9ee

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs https://doi.org/10.1109/ACCESS.2021.3082932

Reference 31

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: 2022 IEEE International Conference on Big Data (Big Data)

Reference 34

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: International Conference on Learning Representations (2019), https://openreview.net/forum?id=HyePrhR5KX

Reference 35

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Advances in neural information pro- cessing systems 30 (2017)

Reference 36

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: International Con- ference on Learning Representations (2021),https://openreview.net/forum?id= KYPz4YsCPj

Reference 37

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining (2025)

Reference 38

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: International Conference on Learning Representations (ICLR) (2020)

Reference 39

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs IEEE Access12, 43460–43484 (2024)

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs In: Pro- ceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining

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Understanding and Improving Laplacian Positional Encodings For Temporal GNNs Advances in Neural Information Processing Systems 36, 67686–67700 (2023)

Reference 43

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