Paper Citation Record · LEDGER

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning

As of 11 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2608.06894.

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

pith.paper-citation-record.v1
2608.06894 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:54:44.059416Z

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation 4281094e-d63b-490d-9824-553b8a03be38 · outbound

This paper cites Advances in Computational Methods and Technologies in Aeronautics and Industry , pages=.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in Computational Methods and Technologies in Aeronautics and Industry , pages=

Reference 1

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Computer Methods in Applied Mechanics and Engineering , volume=

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This paper cites National Science Open , volume=.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning National Science Open , volume=

Reference 3

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This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Fourier Neural Operator for Parametric Partial Differential Equations

Reference 4

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning International Conference on Machine Learning , pages=

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This paper cites Journal of Machine Learning Research , volume=.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Journal of Machine Learning Research , volume=

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This paper cites Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers

Reference 7

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This paper cites Transolver: A Fast Transformer Solver for PDEs on General Geometries.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Transolver: A Fast Transformer Solver for PDEs on General Geometries

Reference 8

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in neural information processing systems , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Neural computation , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning 2008 , publisher=

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Observation 81ed46c4-c619-405c-b1da-0ddd0729472a · outbound

This paper cites DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Reference 12

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This paper cites Nature machine intelligence , volume=.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Nature machine intelligence , volume=

Reference 13

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning ACM/IMS Journal of Data Science , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Journal of Machine Learning Research , volume=

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This paper cites Factorized Fourier Neural Operators.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Factorized Fourier Neural Operators

Reference 16

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in Neural Information Processing Systems , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in Neural Information Processing Systems , volume=

Reference 18

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This paper cites International Conference on Machine Learning , pages=.

From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning International Conference on Machine Learning , pages=

Reference 19

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Simple yet Effective: Low-Rank Spatial Attention for Neural Operators

Reference 21

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning International conference on machine learning , pages=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in Water Resources , volume=

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Reference 24

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in neural information processing systems , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Computer Methods in Applied Mechanics and Engineering , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Nature Machine Intelligence , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning arXiv preprint arXiv:2602.12706 , year=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in neural information processing systems , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Transformer for Partial Differential Equations' Operator Learning

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning International conference on machine learning , pages=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in Neural Information Processing Systems , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Improved Operator Learning by Orthogonal Attention

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in Neural Information Processing Systems , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in neural information processing systems , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Computer Methods in Applied Mechanics and Engineering , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Proceedings of the 2022 Conference of the north American chapter of the Association for Computational Linguistics: human language technologies , pages=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning CViT: Continuous Vision Transformer for Operator Learning

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Reformer: The Efficient Transformer

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Advances in neural information processing systems , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume=

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From Points to Edges: Edge-Conditioned Spectral Operators for Physics-Sensitive PDE Learning Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects

Reference 47

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Pith citing papers

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