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Paper Citation Record · LEDGER

Generalizing to New Dynamical Systems via Frequency Domain Adaptation

As of 8 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2507.00025.

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

pith.paper-citation-record.v1
2507.00025 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

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measured 63 of 63 standing notices

One-hop event checks from named stored sources.

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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

63 of 63 outbound references displayed

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External citation measurements

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Outbound references

Observation ffb5545e-a6cf-46cc-86cf-c52aeec73f8f · outbound

This paper cites Reynolds averaged turbulence modelling using deep neural networks with embedded invariance,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Reynolds averaged turbulence modelling using deep neural networks with embedded invariance,

Reference 1

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Observation a923ef67-d487-4069-966b-10b7ac8aae11 · outbound

This paper cites Discovering governing equations from data by sparse identification of nonlinear dynami- cal systems,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Discovering governing equations from data by sparse identification of nonlinear dynami- cal systems,

Reference 2

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Observation 6708d9b1-330f-42cb-aed2-c2f822ceb4fa · outbound

This paper cites Hidden fluid mechanics: Learning velocity and pressure fields from flow vi- sualizations,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Hidden fluid mechanics: Learning velocity and pressure fields from flow vi- sualizations,

Reference 3

Resolution
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Observation 487d12fd-6291-4f9b-9a5f-66901986616b · outbound

This paper cites Machine learning–accelerated computational fluid dynamics,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Machine learning–accelerated computational fluid dynamics,

Reference 4

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Observation e88851e5-8189-45ef-a043-6ec0e401c139 · outbound

This paper cites Lagrangian fluid simulation with continuous convolutions,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Lagrangian fluid simulation with continuous convolutions,

Reference 5

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Observation 63e2e500-84dc-4147-9dcd-3698baae52db · outbound

This paper cites Can machines learn to predict weather? using deep learning to predict gridded 500- hpa geopotential height from historical weather data,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Can machines learn to predict weather? using deep learning to predict gridded 500- hpa geopotential height from historical weather data,

Reference 6

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Observation b752e228-4ccd-4322-ba85-cf07a7c37274 · outbound

This paper cites FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 7

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Observation b5038991-138d-484a-a7ca-0f7f6cee6ab6 · outbound

This paper cites Inferring halo masses with graph neural networks,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Inferring halo masses with graph neural networks,

Reference 8

Resolution
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Source-reported events for the cited work

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Observation d93b678b-c286-4d16-805a-560f4085131b · outbound

This paper cites Sparsity in continuous-depth neural networks,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Sparsity in continuous-depth neural networks,

Reference 9

Resolution
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Observation 8169a715-0b4d-40c7-b7c0-d94089122add · outbound

This paper cites Physics-Guided Deep Learning for Dynamical Systems: A Survey.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Physics-Guided Deep Learning for Dynamical Systems: A Survey

Reference 10

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Source-reported events for the cited work

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Observation 82c560fd-ebed-4ece-bfb6-2c606257a1ba · outbound

This paper cites Meta-learning dynamics forecast- ing using task inference,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Meta-learning dynamics forecast- ing using task inference,

Reference 11

Resolution
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Observation 51c1889e-f513-4745-a090-71c0757d3165 · outbound

This paper cites Efficient computation of electrograms and ecgs in human whole heart simulations using a reaction- eikonal model,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Efficient computation of electrograms and ecgs in human whole heart simulations using a reaction- eikonal model,

Reference 12

Resolution
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Observation 2faef26f-60ea-471a-972a-a8dc9d558531 · outbound

This paper cites Generalizing to unseen domains: A survey on domain generalization,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Generalizing to unseen domains: A survey on domain generalization,

Reference 13

Resolution
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Observation 85b759f2-b5f6-43b6-bdee-25001e4b9e70 · outbound

This paper cites Leads: Learning dynamical systems that generalize across envi- ronments,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Leads: Learning dynamical systems that generalize across envi- ronments,

Reference 14

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Observation ffd4ccff-8f4d-4fe9-9212-c16b6a5f1b89 · outbound

This paper cites Generalizing to new physical systems via context-informed dynamics model,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Generalizing to new physical systems via context-informed dynamics model,

Reference 15

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Source-reported events for the cited work

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Observation 488280bc-2e6e-4dcd-8c04-dbf8a7799c84 · outbound

This paper cites First-order context-based adaptation for generalizing to new dynamical systems,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation First-order context-based adaptation for generalizing to new dynamical systems,

Reference 16

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Source-reported events for the cited work

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Observation 4a39caba-65b8-4100-b0cf-aab2d74d9f14 · outbound

This paper cites Sequential latent variable models for few-shot high-dimensional time-series forecasting,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Sequential latent variable models for few-shot high-dimensional time-series forecasting,

Reference 17

Resolution
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Observation 2746cc44-7dbc-461b-968a-dede02008fea · outbound

This paper cites Deep learning and transfer learning for device-free human activity recognition: A survey,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Deep learning and transfer learning for device-free human activity recognition: A survey,

Reference 18

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Observation 632684b5-de16-4a97-a147-e4e5c55a8301 · outbound

This paper cites A review of federated meta-learning and its application in cyberspace secu- rity,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation A review of federated meta-learning and its application in cyberspace secu- rity,

Reference 19

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Observation 71e372d9-2404-4360-87fc-ba25afb57aae · outbound

This paper cites An algorithm for the machine calculation of complex fourier series,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation An algorithm for the machine calculation of complex fourier series,

Reference 20

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Source-reported events for the cited work

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Observation 9460fcff-0736-4663-9ec6-15fe17b56744 · outbound

This paper cites Van Loan,Computational frameworks for the fast Fourier transform.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Van Loan,Computational frameworks for the fast Fourier transform

Reference 21

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Generalizing to New Dynamical Systems via Frequency Domain Adaptation Unresolved cited work

Reference 22

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Observation afc083d1-bbf9-412e-b997-382bf79e8475 · outbound

This paper cites Distribu- tionally robust neural networks,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Distribu- tionally robust neural networks,

Reference 23

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Observation f36d5b7d-c950-477b-ab63-32a07829e6cc · outbound

This paper cites Statistics of ro- bust optimization: A generalized empirical likelihood approach,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Statistics of ro- bust optimization: A generalized empirical likelihood approach,

Reference 24

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Observation 8a9b4e62-eaae-4a10-a76a-e81333df1f67 · outbound

This paper cites The risks of invariant risk minimization,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation The risks of invariant risk minimization,

Reference 25

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Source-reported events for the cited work

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Observation 2f997892-6c9d-47bb-bd31-1b2a79f07483 · outbound

This paper cites Out-of-distribution generalization via risk extrapolation (rex),.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Out-of-distribution generalization via risk extrapolation (rex),

Reference 26

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This paper cites Domain agnostic learning with disentangled representations,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Domain agnostic learning with disentangled representations,

Reference 27

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Source-reported events for the cited work

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Observation 8c2d33d5-8b82-4457-889f-ab6347c6c3a7 · outbound

This paper cites Gmfad: Towards gen- eralized visual recognition via multilayer feature alignment and disentanglement,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Gmfad: Towards gen- eralized visual recognition via multilayer feature alignment and disentanglement,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Generalizing to New Dynamical Systems via Frequency Domain Adaptation Learning to generalize: Meta-learning for domain generalization,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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This paper cites Domain generalization via model-agnostic learning of semantic features,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Domain generalization via model-agnostic learning of semantic features,

Reference 30

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 64968d60-6844-4b58-a886-71d97db1cb5d · outbound

This paper cites Generalizing to unseen domains via adversarial data augmentation,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Generalizing to unseen domains via adversarial data augmentation,

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6316e5a8-3bc3-4037-82f6-0679acb11b53 · outbound

This paper cites Domain generalization with mixstyle,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Domain generalization with mixstyle,

Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5ffc63b4-2698-47c9-956b-cd6c5e38d92c · outbound

This paper cites Regular- izing deep networks with semantic data augmentation,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Regular- izing deep networks with semantic data augmentation,

Reference 33

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f05ac34c-50cc-4774-a22d-6657f78934ae · outbound

This paper cites Generalizing to evolving domains with latent structure-aware sequential autoencoder,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Generalizing to evolving domains with latent structure-aware sequential autoencoder,

Reference 34

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d6939300-846c-46f4-8b08-2b85ff919c99 · outbound

This paper cites Training for the future: A simple gradient interpolation loss to generalize along time,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Training for the future: A simple gradient interpolation loss to generalize along time,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.089906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:26.928284Z digest=sha256:573261663273a466910282b26e7c0364f9118e37747a8d14fc4cfe4448f75054

Observation b9e63ff9-6a5f-4cb1-9ded-3ed42de76c08 · outbound

This paper cites Evolving domain generalization via latent structure-aware sequential autoencoder,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Evolving domain generalization via latent structure-aware sequential autoencoder,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.082475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.020975Z digest=sha256:3a2346e172f539e2a8f96a9af319766ba90d2485f195e73a1973d855bb0c1c2a

Observation 7b3e4359-edf9-4a6d-9672-729bfb589741 · outbound

This paper cites Neural ordinary differential equations,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Neural ordinary differential equations,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.074252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.129435Z digest=sha256:97ca59fdc7ee1a6696767ac4292f1a8fdf04071350cb4651c0d8515f8c05515c

Observation 74a3d068-69bb-4a37-b484-b438a7d60b5f · outbound

This paper cites Learning to simulate complex physics with graph networks,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Learning to simulate complex physics with graph networks,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.067065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.241116Z digest=sha256:9804fc542ac65718460e88421210955b547ffbaf17621d9b54fdee53ebcc3775

Observation b5e2f9a9-9c30-434b-9196-4285dc00eb36 · outbound

This paper cites Learning mesh-based simulation with graph networks,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Learning mesh-based simulation with graph networks,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.059369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.347500Z digest=sha256:47ab3200c65015543e2a2eb6d4816e30f03edc16763bdc223d47ed04b46f75cd

Observation 6ad7676a-b3d4-4c7f-871a-690f6aef4ce5 · outbound

This paper cites Learning dynamical systems from data: An introduction to physics-guided deep learning,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Learning dynamical systems from data: An introduction to physics-guided deep learning,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.052017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.455537Z digest=sha256:6ccc4934896f768766a08248361a3378493a4093cd2da432eb6aed7bf88d8011

Observation 5a384640-18cb-4758-9682-c8db7364e38a · outbound

This paper cites Scaling learning algorithms towards ai,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Scaling learning algorithms towards ai,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.044238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.565100Z digest=sha256:f4e6ceb2daae22fbe6a08146e3246515cb9761b5ced6e2a417e5895f97b9f829

Observation 8f39043c-2c76-4433-94e8-677d1aaca998 · outbound

This paper cites Learning long term dependencies via fourier recurrent units,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Learning long term dependencies via fourier recurrent units,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.037342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.677888Z digest=sha256:d92a1542c82042362373659f5a5bd58359c1dd425306cc0880f6f2322cf3116e

Observation a9f7f772-a21f-4790-9bee-e6f8d0ced2bb · outbound

This paper cites Fast training of convolu- tional networks through ffts,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Fast training of convolu- tional networks through ffts,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.029647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.796619Z digest=sha256:d8426935d6a43b93859c1f7a7c88463a27c22c29427e4c7f975f0631a0b2fa26

Observation 03accacc-58ff-4397-966c-ce253a475b7e · outbound

This paper cites Fnet: Mixing tokens with fourier transforms,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Fnet: Mixing tokens with fourier transforms,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.022318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.858572Z digest=sha256:644e0e48e81e99b322e02c6946727e654d008eb650b70256ca940e8ea2f02dcf

Observation 25b53d6d-7b01-48e3-b9fa-328f05598bd5 · outbound

This paper cites Implicit neural representations with periodic activation func- tions,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Implicit neural representations with periodic activation func- tions,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.014504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.892469Z digest=sha256:c6546b3e2128ee2c79e32c10e5407ab94100a98c0e15d40392bc8833ee4b9c31

Observation 83b39e5f-c0a5-4838-b1d5-fbdfe234d0c6 · outbound

This paper cites Robustperiod: Robust time-frequency mining for multiple periodicity detection,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Robustperiod: Robust time-frequency mining for multiple periodicity detection,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:31.006650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:27.995885Z digest=sha256:8e8823bba18ebaac4402b9164c88dfd5b2bdf17952e886089fa94dcb0ec04184

Observation b1458df7-79c5-48da-8e06-575e26d24a48 · outbound

This paper cites Fourier neural operator for parametric partial differential equations,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Fourier neural operator for parametric partial differential equations,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.998445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:28.149757Z digest=sha256:06cac8986a3aebdebaf2d60fe3c97d93fbe7f1440eb5f16cc9bdec52613afe24

Observation b0e83c0b-eb4a-454b-8d24-01e8d839aecf · outbound

This paper cites Learning chaotic dynamics in dissipative systems,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Learning chaotic dynamics in dissipative systems,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.989307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:28.282380Z digest=sha256:798088feaf7917d24acb397dc3ea5e8f16ae77936f7a4b4b3411353c7ce8d251

Observation 88c09841-9f6a-4f9a-a883-4ced9a822e7b · outbound

This paper cites Factorized fourier neural operators,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Factorized fourier neural operators,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.981355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:28.387387Z digest=sha256:27ac54f29dde95af5b46bd646f29a0c5c457eb0eda13bc0424c0d44e7bed5346

Observation 72706d88-49d4-4190-abaa-d47ae7bec6dd · outbound

This paper cites On universal approx- imation and error bounds for fourier neural operators,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation On universal approx- imation and error bounds for fourier neural operators,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.974028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:28.444207Z digest=sha256:460a62b40821f8b05fe1d02d0c64208ca86aae1052d70d42f5b937ae07a07431

Observation 0bb560c5-e25f-4df3-add0-56086da83438 · outbound

This paper cites an unresolved cited work.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:26:30.965532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:28.576590Z digest=sha256:b1d0e098eb2048dc985bec719cb83dea73850591c0ad767ff05c5d6d294b8198

Observation 877292f8-ee43-4973-9ea7-ac26c70dbd53 · outbound

This paper cites Searching for activation functions,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Searching for activation functions,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.957911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:28.697700Z digest=sha256:0b90c5e77190ac4a51f2b362d80462fa150472f7762b4e99a0991e52f7da5182

Observation 68020ba0-317d-418c-aad4-df3ff790befe · outbound

This paper cites Predicting physics in mesh-reduced space with temporal attention,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Predicting physics in mesh-reduced space with temporal attention,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.950198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:28.785970Z digest=sha256:482050d6e57dc12c927e50cbbd560c788d3d2d47fadfbdbad5203f55250502b8

Observation df8328a8-985d-4965-974e-55d858659012 · outbound

This paper cites an unresolved cited work.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:26:30.942498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:28.940294Z digest=sha256:70e6ae0838c193e8f18bdfe0af1ba008f3a9fb16367df88dafb1b5e095e97be8

Observation 50479faf-8a79-4173-ab8b-390c61539aa6 · outbound

This paper cites Efficient inference of parsi- monious phenomenological models of cellular dynamics using s- systems and alternating regression,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Efficient inference of parsi- monious phenomenological models of cellular dynamics using s- systems and alternating regression,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.935024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:29.157703Z digest=sha256:7cf45d04437d2d8ef52900a3b1b4ac63e3eb0138a3c4ed0f1acfeb0b5f1090a7

Observation abc4334c-9e48-46d9-a4f1-d4fae7449ee5 · outbound

This paper cites Complex patterns in a simple system,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Complex patterns in a simple system,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.926668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:29.292540Z digest=sha256:7a6f537fcc8d3f3306ff5ad2f59901cd74e394e1bef587dd2a63d3a2a5ce9593

Observation 8439f4de-71b0-49a5-98ca-3f74b6c774fa · outbound

This paper cites On the effect of the internal friction of fluids on the motion of pendulums,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation On the effect of the internal friction of fluids on the motion of pendulums,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.918883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:29.438189Z digest=sha256:2841c4d62a016c89e72ef8f955ec1a28ac8d6f50ee45b16bba6908437eae1731

Observation 1831eaeb-c9ba-4d8f-b031-faac7893fd60 · outbound

This paper cites Statistical learning theory wiley,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Statistical learning theory wiley,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.910334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:29.617737Z digest=sha256:a5778fe583d8646a2876507d5acfd8299e4408899d3b357510ddc4e26d549812

Observation afeb8ffd-e2fb-4986-af8d-b727d61c2d41 · outbound

This paper cites Automatic differ- entiation in pytorch,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Automatic differ- entiation in pytorch,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.900703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:29.763777Z digest=sha256:c518c39a96c1a1588bb8b6d2e07a31b324f6ebc35cd310e5644ff7433d897d92

Observation 7715d571-6e1e-4e96-80a8-5f94fa7e9ed8 · outbound

This paper cites Adam: A method for stochastic optimiza- tion,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Adam: A method for stochastic optimiza- tion,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.892568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:29.939836Z digest=sha256:f1c2a9508bc4701ff3e7c7039ea1207eb0bcd62bae7b3e3246b2b991c77250f7

Observation c1db9c68-f621-4314-b8c8-6224579079b6 · outbound

This paper cites Fpga dynamic and partial reconfigura- tion: A survey of architectures, methods, and applications,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Fpga dynamic and partial reconfigura- tion: A survey of architectures, methods, and applications,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.883681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:30.058511Z digest=sha256:340d406072a8d5107076d6c1fab20a3c6a16f3173c913bb6ea8ed83e1aeae265

Observation 6a9bbac7-69cc-4fe9-9758-fd88594797aa · outbound

This paper cites Transform once: Efficient operator learning in frequency domain,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Transform once: Efficient operator learning in frequency domain,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:26:30.864228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:30.266608Z digest=sha256:6ed6f47a668a59a0a58f017a54ff512f5fddbfb4bea491b26806b011f97e6b81

Observation e39061bb-f96c-4023-9ef9-692f494c5506 · outbound

This paper cites Physics perception in sloshing scenes with guaranteed thermo- dynamic consistency,.

Generalizing to New Dynamical Systems via Frequency Domain Adaptation Physics perception in sloshing scenes with guaranteed thermo- dynamic consistency,

Reference 63

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T00:26:30.646554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:26:30.415242Z digest=sha256:88771d28a66813ce69e67c1deb3948b6a0c4cbbb6af9e84d128794e7b782e935

Pith citing papers

No inbound Pith citation observations are available.