Paper Citation Record · LEDGER

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport

As of 21 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2506.22204.

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

pith.paper-citation-record.v1
2506.22204 v1

Coverage vector

measured 28 of 28 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-06T22:15:33.831589Z

measured 28 of 28 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

28 of 28 outbound references displayed

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Outbound references

Observation a23e228d-38bf-474d-b4ac-27dfa893261e · outbound

This paper cites A hybrid simulation of DNN -based gray box models.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport A hybrid simulation of DNN -based gray box models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:37.960663Z

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Observation b971a928-4bdf-453c-9b2b-7a7e21755b66 · outbound

This paper cites Wasserstein generative adversarial networks.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Wasserstein generative adversarial networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T22:15:31.149866Z

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Observation e4452bfc-288d-4c47-8ac1-8abab736da2c · outbound

This paper cites Backhoff-Veraguas, M.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Backhoff-Veraguas, M

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:37.824966Z

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Observation 8b710af3-117a-4465-9b36-20738c45d485 · outbound

This paper cites Applications of weak transport theory.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Applications of weak transport theory

Reference 4

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Observation 4689b2c5-e1ab-4dad-92e3-91a8624870d3 · outbound

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Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:15:37.676357Z

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Observation 48916377-9d0b-4933-a563-da7cfa5fe0c9 · outbound

This paper cites Physics-informed learning of governing equations from scarce data.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Physics-informed learning of governing equations from scarce data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:37.521228Z

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Observation 370c1a9e-8e2d-4e53-9a56-80c2e0bef682 · outbound

This paper cites Kantorovich duality for general transport costs and applications.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Kantorovich duality for general transport costs and applications

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:37.364364Z

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Observation 97254a2f-bf24-41d3-a1e0-1d6d191873ac · outbound

This paper cites Borgwardt, Malte J.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Borgwardt, Malte J

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:37.249330Z

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Observation 735177a5-a714-4060-b28e-2d9574008701 · outbound

This paper cites Improved training of wasserstein gans.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Improved training of wasserstein gans

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:37.113997Z

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Observation 1bf13019-fb94-4dac-be28-beac33281be2 · outbound

This paper cites Unifying model-based and neural network feedforward: Physics-guided neural networks with linear autoregressive dynamics.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Unifying model-based and neural network feedforward: Physics-guided neural networks with linear autoregressive dynamics

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:36.985461Z

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Observation 93da1a25-90da-4bde-becf-b5214ce6d7fd · outbound

This paper cites Kernel neural optimal transport.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Kernel neural optimal transport

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:36.798339Z

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Observation 499618a4-3a92-4913-b6b7-b565809008ab · outbound

This paper cites Neural optimal transport.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Neural optimal transport

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:36.647007Z

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Observation 11a09db4-181d-444b-a442-aba4a46c6323 · outbound

This paper cites Revisiting classifier two-sample tests.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Revisiting classifier two-sample tests

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:36.487210Z

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Observation ef9aafe0-fed1-476b-8e9f-680df7f206bf · outbound

This paper cites Boyer, Egemen Kolemen, and Jeff G.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Boyer, Egemen Kolemen, and Jeff G

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:36.303364Z

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Observation f849760e-2e92-40e0-8111-d14536d6d6b2 · outbound

This paper cites Psichogios and Lyle H.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Psichogios and Lyle H

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:36.091955Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6243d781-6c90-4ecf-aab0-c98649933fa9 · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:35.960322Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eceb5072-2a7f-4b98-8906-eb09db2cf5f4 · outbound

This paper cites Rico-Martinez, J.S.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Rico-Martinez, J.S

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:35.763911Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bf3d46ea-9774-4044-96ba-ee20aa878ca9 · outbound

This paper cites Generative modeling with optimal transport maps.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Generative modeling with optimal transport maps

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:35.579208Z

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Observation 5aba6329-08b3-464c-b7be-c5196e5de1ff · outbound

This paper cites MMD aggregated two-sample test.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport MMD aggregated two-sample test

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:35.430766Z

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Observation 7b1ad858-a4b4-46b9-adaa-c428ce7f5532 · outbound

This paper cites Physics-integrated variational autoencoders for robust and interpretable generative modeling.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Physics-integrated variational autoencoders for robust and interpretable generative modeling

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:35.244099Z

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Observation 2176944c-3222-4fb5-a321-5213a08aa784 · outbound

This paper cites Deep grey-box modeling with adaptive data-driven models toward trustworthy estimation of theory-driven models.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Deep grey-box modeling with adaptive data-driven models toward trustworthy estimation of theory-driven models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:35.004974Z

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Observation 589818cb-83a5-417a-8bf0-369a24b7a7f5 · outbound

This paper cites Thompson and Mark A.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Thompson and Mark A

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:34.856260Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f0e99af0-1c23-41a5-889f-3a656e97ac50 · outbound

This paper cites p ^3 vae: a physics-integrated generative model.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport p ^3 vae: a physics-integrated generative model

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:34.673292Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 83b76e21-9a86-4d51-bc0c-abe94a638321 · outbound

This paper cites Clim ODE : Climate and weather forecasting with physics-informed neural ODE s.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Clim ODE : Climate and weather forecasting with physics-informed neural ODE s

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:34.534549Z

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Observation 51a664d3-df11-4a50-b1e0-661de72cb0cf · outbound

This paper cites an unresolved cited work.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:15:34.360489Z

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Observation 7380f67b-245c-442f-a7c4-106f94bf9160 · outbound

This paper cites Robust hybrid learning with expert augmentation.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Robust hybrid learning with expert augmentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:34.198578Z

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Observation 94ac5d80-aae0-4230-b788-5a9c269ae1a1 · outbound

This paper cites Augmenting physical models with deep networks for complex dynamics forecasting.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport Augmenting physical models with deep networks for complex dynamics forecasting

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:15:34.024877Z

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Observation fd361296-e0be-4df7-8b86-074b6edc6235 · outbound

This paper cites write newline.

Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport write newline

Reference 28

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Pith citing papers

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