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Paper Citation Record · LEDGER

Lagrangian Neural Networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 62 inbound Pith citation observations for arXiv:2003.04630.

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

pith.paper-citation-record.v1
2003.04630 v2

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measured 62 of 62 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 62 of 62 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:11:42.863833Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

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External citation measurements

66
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

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Pith citing papers

Observation 60b6f0c2-d989-42d4-b1e6-ff587c858824 · inbound

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges cites this paper.

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Lagrangian Neural Networks

Reference 20

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arxiv_id, observed 2026-05-13T02:39:29.580545Z

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Observation 9165b508-51ae-44a2-8974-0f17f202db37 · inbound

SLIDE: A machine-learning based method for forced dynamic response estimation of multibody systems cites this paper.

SLIDE: A machine-learning based method for forced dynamic response estimation of multibody systems Lagrangian Neural Networks

Reference 11

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arxiv_id, observed 2026-05-23T20:43:25.636909Z

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Observation 713d2c43-4b40-4250-a2a8-b577c2d2d57c · inbound

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics cites this paper.

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics Lagrangian Neural Networks

Reference 2

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Observation 1105abdb-0223-456d-ba8c-320aea864c80 · inbound

Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints cites this paper.

Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints Lagrangian Neural Networks

Reference 1996

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Observation 246a17f6-32de-436f-bd24-25774f7a07d9 · inbound

Learning long range dependencies through time reversal symmetry breaking cites this paper.

Learning long range dependencies through time reversal symmetry breaking Lagrangian Neural Networks

Reference 40

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Observation a6534924-5a52-4df7-815e-bc8bbd1c2b40 · inbound

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates cites this paper.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Lagrangian Neural Networks

Reference 17

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Observation 2b4dfeac-babb-4072-a533-2cf50c7ad473 · inbound

Symmetry-preserving neural networks in lattice field theories cites this paper.

Symmetry-preserving neural networks in lattice field theories Lagrangian Neural Networks

Reference 58

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Observation 6b3b7e8f-7173-43a7-9f7b-6125883d8996 · inbound

Investigating Lagrangian Neural Networks for Infinite Horizon Planning in Quadrupedal Locomotion cites this paper.

Investigating Lagrangian Neural Networks for Infinite Horizon Planning in Quadrupedal Locomotion Lagrangian Neural Networks

Reference 7

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Observation 068098cc-ebb1-4743-b179-549eb2411be2 · inbound

Newtonian and Lagrangian Neural Networks: A Comparison Towards Efficient Inverse Dynamics Identification cites this paper.

Newtonian and Lagrangian Neural Networks: A Comparison Towards Efficient Inverse Dynamics Identification Lagrangian Neural Networks

Reference 8

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Observation faca84bf-683c-475c-9ff2-e20cfba15468 · inbound

AI4Research: A Survey of Artificial Intelligence for Scientific Research cites this paper.

AI4Research: A Survey of Artificial Intelligence for Scientific Research Lagrangian Neural Networks

Reference 151

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Observation 5a623df9-4330-40ac-a755-12ff3d79c87b · inbound

Discovering Interpretable Ordinary Differential Equations from Noisy Data cites this paper.

Discovering Interpretable Ordinary Differential Equations from Noisy Data Lagrangian Neural Networks

Reference 16

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Observation 320bf30d-4f71-446b-a401-13b2bc5655fe · inbound

Data Readiness for Scientific AI at Scale cites this paper.

Data Readiness for Scientific AI at Scale Lagrangian Neural Networks

Reference 10

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Observation 8cf254c3-f6d3-4516-ac74-d070a25f807c · inbound

Structure-Preserving Digital Twins via Conditional Neural Whitney Forms cites this paper.

Structure-Preserving Digital Twins via Conditional Neural Whitney Forms Lagrangian Neural Networks

Reference 26

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Observation df8b6b89-46c5-49ea-9211-56e8cd5b1e49 · inbound

Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach cites this paper.

Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach Lagrangian Neural Networks

Reference 13

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Observation 25a5bddc-378c-4440-9ef9-739a0535bdb3 · inbound

Optimal transport by a Lagrangian dynamics of population distribution cites this paper.

Optimal transport by a Lagrangian dynamics of population distribution Lagrangian Neural Networks

Reference 29

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Observation 428e1abe-f59e-4261-8a2d-d93441fa1fd4 · inbound

When is a System Discoverable from Data? Discovery Requires Chaos cites this paper.

When is a System Discoverable from Data? Discovery Requires Chaos Lagrangian Neural Networks

Reference 43

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Observation 4799b1bd-c5df-46f9-8854-836f120892d3 · inbound

Gradient Networks for Universal Magnetic Modeling of Synchronous Machines cites this paper.

Gradient Networks for Universal Magnetic Modeling of Synchronous Machines Lagrangian Neural Networks

Reference 22

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Observation 355aceaf-33af-4e7d-b6bf-b0d4345d23bd · inbound

A hierarchy of thermodynamics learning frameworks for inelastic constitutive modeling cites this paper.

A hierarchy of thermodynamics learning frameworks for inelastic constitutive modeling Lagrangian Neural Networks

Reference 21

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Parametric Interpolation of Dynamic Mode Decomposition for Predicting Nonlinear Systems cites this paper.

Parametric Interpolation of Dynamic Mode Decomposition for Predicting Nonlinear Systems Lagrangian Neural Networks

Reference 6

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Observation f0826f25-7ece-4e31-898c-f381d1f9605b · inbound

Dissipative Latent Residual Physics-Informed Neural Networks for Modeling and Identification of Electromechanical Systems cites this paper.

Dissipative Latent Residual Physics-Informed Neural Networks for Modeling and Identification of Electromechanical Systems Lagrangian Neural Networks

Reference 29

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Mesh Field Theory: Port-Hamiltonian Formulation of Mesh-Based Physics cites this paper.

Mesh Field Theory: Port-Hamiltonian Formulation of Mesh-Based Physics Lagrangian Neural Networks

Reference 24

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Observation 8b44c324-18d8-4cc9-89b2-88e054a74506 · inbound

Physically Native World Models: A Hamiltonian Perspective on Generative World Modeling cites this paper.

Physically Native World Models: A Hamiltonian Perspective on Generative World Modeling Lagrangian Neural Networks

Reference 4

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Observation de84d6b3-7ec1-4151-8390-abdf6e847efa · inbound

Physically Native World Models: A Hamiltonian Perspective on Generative World Modeling cites this paper.

Physically Native World Models: A Hamiltonian Perspective on Generative World Modeling Lagrangian Neural Networks

Reference 4

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arxiv_id, observed 2026-07-01T08:15:31.837835Z

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Observation 84986a26-45af-4cb6-af37-471c97a36643 · inbound

Physically Native World Models: A Hamiltonian Perspective on Generative World Modeling cites this paper.

Physically Native World Models: A Hamiltonian Perspective on Generative World Modeling Lagrangian Neural Networks

Reference 4

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Detecting Deepfakes via Hamiltonian Dynamics cites this paper.

Detecting Deepfakes via Hamiltonian Dynamics Lagrangian Neural Networks

Reference 15

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arxiv_id, observed 2026-05-09T06:50:39.837074Z

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LaWM: Least Action World Models for Long-Horizon Physical Consistency from Visual Observations cites this paper.

LaWM: Least Action World Models for Long-Horizon Physical Consistency from Visual Observations Lagrangian Neural Networks

Reference 6

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Support-Safe Variational Hybrid Filtering for Contact-Mode and Sparse-Law Recovery cites this paper.

Support-Safe Variational Hybrid Filtering for Contact-Mode and Sparse-Law Recovery Lagrangian Neural Networks

Reference 27

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arxiv_id, observed 2026-05-20T21:19:02.947803Z

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Physics-Informed Graph Neural Network Surrogates for Turbulent Nanoparticle Dispersion in Dental Clinical Environments cites this paper.

Physics-Informed Graph Neural Network Surrogates for Turbulent Nanoparticle Dispersion in Dental Clinical Environments Lagrangian Neural Networks

Reference 80

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Mechanisms of Misgeneralization in Physical Sequence Modeling cites this paper.

Mechanisms of Misgeneralization in Physical Sequence Modeling Lagrangian Neural Networks

Reference 14

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Learning First Integrals via Backward-Generated Data and Guided Reinforcement Learning cites this paper.

Learning First Integrals via Backward-Generated Data and Guided Reinforcement Learning Lagrangian Neural Networks

Reference 20

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Integrable Elasticity via Neural Demand Potentials cites this paper.

Integrable Elasticity via Neural Demand Potentials Lagrangian Neural Networks

Reference 68

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arxiv_id, observed 2026-05-22T06:34:41.038662Z

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Learning partially observed systems with neural Hamiltonian ordinary differential equations cites this paper.

Learning partially observed systems with neural Hamiltonian ordinary differential equations Lagrangian Neural Networks

Reference 36

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arxiv_id, observed 2026-05-25T05:10:22.173953Z

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A comparative study of accuracy and rollout stability of temporal surrogate models cites this paper.

A comparative study of accuracy and rollout stability of temporal surrogate models Lagrangian Neural Networks

Reference 4

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arxiv_id, observed 2026-06-30T12:34:38.560085Z

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Observation ee6801de-f74c-4915-8505-16d410ae128f · inbound

L-Learning : A Lyapunov-Based Approach Leveraging Lagrangian Mechanics for Efficient and Stable Robot Tracking cites this paper.

L-Learning : A Lyapunov-Based Approach Leveraging Lagrangian Mechanics for Efficient and Stable Robot Tracking Lagrangian Neural Networks

Reference 20

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arxiv_id, observed 2026-06-29T17:23:44.885000Z

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Observation 81379823-335e-47ab-b6fb-5f9ff1b6d0fd · inbound

NeuROK: Generative 4D Neural Object Kinematics cites this paper.

NeuROK: Generative 4D Neural Object Kinematics Lagrangian Neural Networks

Reference 23

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arxiv_id, observed 2026-06-29T08:23:15.026492Z

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Observation 2bd373fa-482e-4af6-ae2d-5a72c46cf54b · inbound

Hamiltonian-Inspired Attention Mechanism for Scalable RF Transmitter Fingerprinting cites this paper.

Hamiltonian-Inspired Attention Mechanism for Scalable RF Transmitter Fingerprinting Lagrangian Neural Networks

Reference 5

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arxiv_id, observed 2026-06-30T19:25:01.067560Z

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Observation c576054f-ef7b-47ec-8614-4d16d3215cc8 · inbound

Attention-based optimizer for symmetry finding cites this paper.

Attention-based optimizer for symmetry finding Lagrangian Neural Networks

Reference 28

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arxiv_id, observed 2026-06-29T14:33:31.318018Z

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

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Observation f39a9847-c6a8-4b21-a100-31e1a74e318e · inbound

Physically Viable World Models: A Case for Query-Conditioned Embodied AI cites this paper.

Physically Viable World Models: A Case for Query-Conditioned Embodied AI Lagrangian Neural Networks

Reference 17

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arxiv_id, observed 2026-06-29T09:13:16.495726Z

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 705c9eb6-5c95-4b48-919f-94ad3d6f1bdf · inbound

Learning Transferable Predictability Representations cites this paper.

Learning Transferable Predictability Representations Lagrangian Neural Networks

Reference 1

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arxiv_id, observed 2026-06-29T08:33:15.421701Z

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=2026-06-29T08:28:05.491771Z digest=sha256:aefc581b7039f541388c737b3118d1a3bdc8a6a82f8601653f4857bbc049a718

Observation b0fe2b7a-b193-44b3-a4a7-a6965d14b0e7 · inbound

Can Predicted Dynamics Exist in the Physical World? cites this paper.

Can Predicted Dynamics Exist in the Physical World? Lagrangian Neural Networks

Reference 30

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arxiv_id, observed 2026-06-30T13:04:40.053328Z

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=2026-06-30T13:02:21.832944Z digest=sha256:dbc6c91b225ca576b8dc41d6f5fce9be53d6901ff45906bd6c6a928b44a586ba

Observation ab8e69cb-89c9-4499-a22a-b6d287730df3 · inbound

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications cites this paper.

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications Lagrangian Neural Networks

Reference 191

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arxiv_id, observed 2026-06-29T08:43:15.597875Z

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=2026-06-29T08:36:23.776293Z digest=sha256:666aeb739b9b5878885ba8bc93d7ce5fddfbd525e862874feebc006c8fc6ab7f

Observation 315355e2-5786-40d6-8e76-f5e9026ed2fd · inbound

Robots Need More than VLA and World Models cites this paper.

Robots Need More than VLA and World Models Lagrangian Neural Networks

Reference 52

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arxiv_id, observed 2026-07-02T13:46:59.283272Z

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 1b79c12a-378b-4871-9f10-3c38c5628e09 · inbound

GENERIC-FNO: Embedding Energy Conservation and Entropy Production into Fourier Neural Operators cites this paper.

GENERIC-FNO: Embedding Energy Conservation and Entropy Production into Fourier Neural Operators Lagrangian Neural Networks

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T14:44:31.587270Z digest=sha256:8b8a05434e13d7fa846c158029159b47c8e5b0f784b9e9df6849eb8c14d244b8

Observation 1e7065bb-c480-4d2f-b108-10b3e67789f4 · inbound

Between Amnesia and Chaos: A Memory Stability Expressivity Trilemma for Trainable Dissipative Oscillator Networks cites this paper.

Between Amnesia and Chaos: A Memory Stability Expressivity Trilemma for Trainable Dissipative Oscillator Networks Lagrangian Neural Networks

Reference 2

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arxiv_id, observed 2026-07-02T22:37:26.582862Z

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 02e4ebc7-8546-45e8-946c-134c9f1ea218 · inbound

Embedding Hybrid Systems into Continuous Latent Vector Fields cites this paper.

Embedding Hybrid Systems into Continuous Latent Vector Fields Lagrangian Neural Networks

Reference 77

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arxiv_id, observed 2026-07-03T04:17:37.094073Z

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=arxiv_source observed=2026-06-27T14:04:40.078357Z digest=sha256:da8ae26f83a7f530e0fbb2986f0b47321475eda8d29054a86f5979762bd19343

Observation 1495a2bc-96d8-4030-b2ff-f1a56233359d · inbound

Mechanical Field Networks: Structured Neural Dynamics for Multivariate Systems cites this paper.

Mechanical Field Networks: Structured Neural Dynamics for Multivariate Systems Lagrangian Neural Networks

Reference 4

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arxiv_id, observed 2026-06-27T17:21:06.732703Z

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=2026-06-27T17:17:22.959696Z digest=sha256:1e5dac7c7276c42166fd0635f06daeeb6125b8a97232b17acbb4e6a9f501f93b

Observation 5e13a9d0-b836-4ea2-939f-6f41d4f2d41e · inbound

Least-Action-Guided Diffusion for Physical Extrapolation cites this paper.

Least-Action-Guided Diffusion for Physical Extrapolation Lagrangian Neural Networks

Reference 45

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arxiv_id, observed 2026-07-03T03:57:38.673947Z

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=arxiv_source observed=2026-06-27T14:20:43.478834Z digest=sha256:721dfff67d401d32fa697afb03737283514e7de40eb7f4a5c328ac2b8b10316a

Observation 3cf0e1ae-7119-4a19-b93b-6b9a802f6422 · inbound

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics cites this paper.

NEXUS: Neural Energy Fields for Physically Consistent Contact-Rich 3D Object Dynamics Lagrangian Neural Networks

Reference 46

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arxiv_id, observed 2026-07-03T17:18:43.379948Z

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 43754c74-259f-4d5b-aeeb-0b93cec96efd · inbound

Locally Stable Neural ODEs with Characterized Region of Attraction cites this paper.

Locally Stable Neural ODEs with Characterized Region of Attraction Lagrangian Neural Networks

Reference 16

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arxiv_id, observed 2026-07-04T02:09:22.488325Z

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 6003b2a7-5924-4c91-8f20-fcb66fc50f12 · inbound

SPADE: Structure-Prior Adaptive Decision Estimation cites this paper.

SPADE: Structure-Prior Adaptive Decision Estimation Lagrangian Neural Networks

Reference 8

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arxiv_id, observed 2026-07-04T10:49:45.819248Z

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=arxiv_source observed=2026-06-26T08:30:06.424919Z digest=sha256:4a5e89ff699cd618f77844c7c34260a42e39d4615974d779f64c12f89b2885b8

Observation df3e4efa-db56-4beb-bca2-2587fdffece9 · inbound

Symplectic Neural Networks for Learning Non-Separable Hamiltonians cites this paper.

Symplectic Neural Networks for Learning Non-Separable Hamiltonians Lagrangian Neural Networks

Reference 19

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arxiv_id, observed 2026-07-04T13:09:50.195303Z

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=2026-06-26T05:32:31.826331Z digest=sha256:ae0195ae623b23b9a16ac6751579e8315f33314b7d2952abaf21668db0c0d5ba

Observation b0a830b7-7288-496e-a7c4-70c44ceee8e3 · inbound

Geometry-Conditioned Fourier Neural Operators for Cubic Nonlinear Schrodinger Dynamics on Periodic Domains cites this paper.

Geometry-Conditioned Fourier Neural Operators for Cubic Nonlinear Schrodinger Dynamics on Periodic Domains Lagrangian Neural Networks

Reference 5

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arxiv_id, observed 2026-07-01T19:06:02.780695Z

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=2026-06-29T01:13:24.648957Z digest=sha256:c406b0d66beb509a35a9c99f61fcb90ce167bfe7948aa5e4485a0cd5f7ecb44a

Observation 9169286c-3a98-44ef-8437-fef5f692fff9 · inbound

Geometry-Conditioned Fourier Neural Operators for Cubic Nonlinear Schrodinger Dynamics on Periodic Domains cites this paper.

Geometry-Conditioned Fourier Neural Operators for Cubic Nonlinear Schrodinger Dynamics on Periodic Domains Lagrangian Neural Networks

Reference 5

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no resolver link, observed 2026-08-02T10:01:14.280240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:01:14.280240Z digest=sha256:e05a106f9628e52108ee5169ed9855b707700003ac6ad36ea3ab9a7dc7478460

Observation 00b243d4-933d-4895-b6bf-16b641b7b1f2 · inbound

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts cites this paper.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Lagrangian Neural Networks

Reference 24

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local_arxiv, observed 2026-07-10T20:37:34.100194Z

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 0f68e131-3f77-42d1-9f34-61275822a3c1 · inbound

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts cites this paper.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Lagrangian Neural Networks

Reference 23

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no resolver link, observed 2026-08-02T08:18:14.251072Z

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source=pdf_text observed=2026-08-02T08:18:14.251072Z digest=sha256:f8e40a93634877c351086d7cdbf322b6ba2cf8ccd108f13af41df7e735f83953

Observation bb3c5dfd-5fd9-4cc1-a13f-ec17984e2105 · inbound

The Equilibrium Is the Initialization: Lazy Identity Collapse in Physics-Structured Deep Equilibrium Reasoning cites this paper.

The Equilibrium Is the Initialization: Lazy Identity Collapse in Physics-Structured Deep Equilibrium Reasoning Lagrangian Neural Networks

Reference 15

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no resolver link, observed 2026-07-14T06:57:31.514910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T06:57:31.514910Z digest=sha256:a2953775880c3cb59c06d6f51e114059387ac14407246aec1ac4b6a2200e952a

Observation 942ae050-e93b-400a-bd42-6f3095b2a4ef · inbound

Quantum Port-Hamiltonian Neural Networks: Learning Conservative and Dissipative Dynamics via Measurement-Induced Nonlinearity cites this paper.

Quantum Port-Hamiltonian Neural Networks: Learning Conservative and Dissipative Dynamics via Measurement-Induced Nonlinearity Lagrangian Neural Networks

Reference 9

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no resolver link, observed 2026-08-02T06:43:04.496203Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:43:04.496203Z digest=sha256:37e331a910b71a156eb4fc70d795eab7a50d04bc0332fdec46e38f30a8b440cc

Observation 1ee29e78-f723-4f02-b5b1-bfdac64ea9de · inbound

Can AI Follow In Einstein's Footsteps? cites this paper.

Can AI Follow In Einstein's Footsteps? Lagrangian Neural Networks

Reference 69

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T01:19:20.508941Z digest=sha256:aa0993d42fc9597ab3185e5d04e97d14246bd13be46292dded0093972e17778b

Observation 770d980f-c382-49c2-8ab2-7742c173b427 · inbound

Data-free neural PDE solvers based on Graph Neural Networks and weak forms cites this paper.

Data-free neural PDE solvers based on Graph Neural Networks and weak forms Lagrangian Neural Networks

Reference 25

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no resolver link, observed 2026-07-31T23:24:57.257098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:24:57.257098Z digest=sha256:2efdbdfbb9d050830ba6a4379ceec261fef4d12644bb125d391903eab3ab92fd

Observation c41706e8-5958-4f8b-bbb7-5e64b247e111 · inbound

Latent Lie-Poisson Neural Networks (LLPNNs): Discovering the motion of Lie-Poisson systems through observable data and latent dynamics cites this paper.

Latent Lie-Poisson Neural Networks (LLPNNs): Discovering the motion of Lie-Poisson systems through observable data and latent dynamics Lagrangian Neural Networks

Reference 9

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no resolver link, observed 2026-08-03T16:56:03.381502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:56:03.381502Z digest=sha256:61804be3958e6bc91f7a3758c78fb785ce3bb1de6ae0616378ffdb73a77bb763

Observation a203138d-53f4-4125-86eb-b3661b831a9d · inbound

Implicit Machine Learning Force Fields Accelerate Molecular Dynamics Simulations cites this paper.

Implicit Machine Learning Force Fields Accelerate Molecular Dynamics Simulations Lagrangian Neural Networks

Reference 69

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no resolver link, observed 2026-08-03T12:39:58.517973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:39:58.517973Z digest=sha256:0f3ee465d76a890b3baa568941163793b7262adfc752057d8e9ed45236640375

Observation 95187239-45bb-4113-aa9f-ee057b592ac9 · inbound

HyperODE: Zero-Shot Surrogate for Simulation and Inference of Dynamical Systems cites this paper.

HyperODE: Zero-Shot Surrogate for Simulation and Inference of Dynamical Systems Lagrangian Neural Networks

Reference 42

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no resolver link, observed 2026-08-05T00:22:20.578549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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