Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network | Paper Citation Record

Observation 6e381245-defe-400f-bcb6-b120c7879ba4 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network , " * write output.state after.block = add.period write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T05:12:33.051187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 540cb419-e0c4-496c-8fcc-7363cc0e2fd4 · outbound

This paper cites write newline.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network write newline

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T05:12:33.056007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80d69706-9676-45bb-92b8-515369cecc47 · outbound

This paper cites Structural Control and Health Monitoring 24 (3), e1889.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Structural Control and Health Monitoring 24 (3), e1889

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.690641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cbbe1858-3914-41d6-8c25-df52aa031853 · outbound

This paper cites Computational Mechanics 64 (2), 525--545.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Computational Mechanics 64 (2), 525--545

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.680023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a7d985ac-d34a-4a90-a8e6-6e124fb8c457 · outbound

This paper cites Computers & fluids 35 (3), 326--348.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Computers & fluids 35 (3), 326--348

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.668836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9887e6f4-a20a-41de-a3de-306aaa9b228d · outbound

This paper cites Proceedings of the national academy of sciences 113 (15), 3932--3937.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Proceedings of the national academy of sciences 113 (15), 3932--3937

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.657482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f7f4740f-6188-46cc-a8c8-b2388023c999 · outbound

This paper cites IEEE Transactions on Power Systems.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network IEEE Transactions on Power Systems

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.645228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation afa1d998-f8c5-4c89-be72-a5ba2b24fc48 · outbound

This paper cites In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI)\/ , pp.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI)\/ , pp

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.633551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b1d7d968-4fa6-4ff2-92f6-42abb279a04e · outbound

This paper cites Computer Methods in Applied Mechanics and Engineering 365 , 113000.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Computer Methods in Applied Mechanics and Engineering 365 , 113000

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.621684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3f5827f1-f89c-4c3b-824c-dc2b59d22ff3 · outbound

This paper cites The Annals of Statistics pp.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network The Annals of Statistics pp

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.610434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8616e217-fe03-4da5-aacb-9734beaf09d3 · outbound

This paper cites Physics of Fluids 31 (12), 125111.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Physics of Fluids 31 (12), 125111

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.599664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b6cb4b02-1909-4cd6-b155-5ef6d80a8cdd · outbound

This paper cites Strain 55 (1), e12297.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Strain 55 (1), e12297

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.589278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6a833cb1-e40f-43fc-9a06-6f05d4449816 · outbound

This paper cites Deep Learning the Physics of Transport Phenomena.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Deep Learning the Physics of Transport Phenomena

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T05:12:33.100841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd99360-a3b8-43f8-9221-4ac082a66962 · outbound

This paper cites Multi-fidelity Generative Deep Learning Turbulent Flows.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Multi-fidelity Generative Deep Learning Turbulent Flows

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T05:12:33.105165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc67d536-56eb-4686-ae24-ae0047390b23 · outbound

This paper cites In Proceedings of the thirteenth international conference on artificial intelligence and statistics\/ , pp.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network In Proceedings of the thirteenth international conference on artificial intelligence and statistics\/ , pp

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.579050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 473d7e82-116b-4562-8485-9255ad78acad · outbound

This paper cites Communications of the ACM 63 (11), 139--144.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Communications of the ACM 63 (11), 139--144

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.566138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2536d881-d34b-4b4f-aff7-9b91f12d3a88 · outbound

This paper cites In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining\/ , pp.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining\/ , pp

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.555662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 417d2c33-f242-4047-83a7-fdaeaebce14d · outbound

This paper cites Computer Methods in Applied Mechanics and Engineering 318 , 382--411.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Computer Methods in Applied Mechanics and Engineering 318 , 382--411

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.543844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 48e11fa7-1e04-4977-90e6-1052cfe68905 · outbound

This paper cites In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)\/ , pp.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)\/ , pp

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.532086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a044ba75-d5bf-4bc0-b3e7-20fff6547db9 · outbound

This paper cites Proceedings of the Royal Society A 476 (2242), 20200279.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Proceedings of the Royal Society A 476 (2242), 20200279

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.520752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c7e9b9b1-aa65-46ef-ab67-710f76a0ab2e · outbound

This paper cites Auto-Encoding Variational Bayes.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Auto-Encoding Variational Bayes

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T05:12:33.130480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd319b5f-27e0-4f3b-990f-7424ff75b96f · outbound

This paper cites Physical Review E 100 (2), 022220.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Physical Review E 100 (2), 022220

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.509318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c0d1696b-44d4-4214-bec2-054fad009c2f · outbound

This paper cites Journal of Wind Engineering and Industrial Aerodynamics 172 , 196--211.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Journal of Wind Engineering and Industrial Aerodynamics 172 , 196--211

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.498524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7db19dba-80c7-4f11-a328-e094f96c467c · outbound

This paper cites Engineering Structures 155 , 1--15.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Engineering Structures 155 , 1--15

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.487163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 94a76758-b897-48d9-a47e-7e07ae1054b6 · outbound

This paper cites Nonlinear Dynamics 106 (4), 3231--3246.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Nonlinear Dynamics 106 (4), 3231--3246

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.474519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3c75cdd3-d3c9-4821-8775-bc93725bf482 · outbound

This paper cites Nonlinear Dynamics 105 (4), 3409--3422.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Nonlinear Dynamics 105 (4), 3409--3422

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.463869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 549859db-c885-45ae-aa67-eb0d3306e609 · outbound

This paper cites Nature communications 9 (1), 1--10.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Nature communications 9 (1), 1--10

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.452649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 43907384-3db1-4aa0-bb36-1ea35fc7475f · outbound

This paper cites Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders

Reference 28

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T05:12:33.282890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4f4a1b0a-4fd4-48dd-b504-209d58e8c643 · outbound

This paper cites Computers & Fluids 32 (3), 337--352.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Computers & Fluids 32 (3), 337--352

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.441290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2859fc93-1471-41d5-b2ab-8f8a05df5713 · outbound

This paper cites Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (6), 063116.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (6), 063116

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.429625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 639eeb4e-fab3-4766-ad5f-a870a3cc8495 · outbound

This paper cites Science 367 (6481), 1026--1030.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Science 367 (6481), 1026--1030

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T05:12:33.167170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9054d3d-ed70-49d4-9d4b-54373b88468e · outbound

This paper cites IEEE Transactions on Power Systems 34 (6), 5044--5052.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network IEEE Transactions on Power Systems 34 (6), 5044--5052

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.411385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d5d32804-cdcd-4b28-8ab2-127c5bd73fc1 · outbound

This paper cites Robotics and Autonomous Systems 124 , 103386.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Robotics and Autonomous Systems 124 , 103386

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.399727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d2bb5070-fed3-4c45-987f-e1cf51983f5d · outbound

This paper cites Journal of Design Studio 6 (2), 325--335.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Journal of Design Studio 6 (2), 325--335

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.387988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 068ba817-b8ed-499b-aec4-a52a1560ba51 · outbound

This paper cites Journal of Design Studio 6 (2), 383--395.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Journal of Design Studio 6 (2), 383--395

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.375760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 52e6ce0e-84c9-4192-9b1c-86b61d79b71b · outbound

This paper cites Machine Learning Approach to Model Order Reduction of Nonlinear Systems via Autoencoder and LSTM Networks.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Machine Learning Approach to Model Order Reduction of Nonlinear Systems via Autoencoder and LSTM Networks

Reference 36

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T05:12:33.264585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5fec07ff-c0c1-45a2-84db-d4edd3cdcea2 · outbound

This paper cites Data-Driven, Physics-Based Feature Extraction from Fluid Flow Fields.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Data-Driven, Physics-Based Feature Extraction from Fluid Flow Fields

Reference 37

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T05:12:33.245965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4ce0071b-ccee-4f93-855d-b7979f0b5226 · outbound

This paper cites Mechanical Systems and Signal Processing 166 , 108473.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Mechanical Systems and Signal Processing 166 , 108473

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.363962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 26c14936-077c-4ca1-9f27-ae5244212dbd · outbound

This paper cites In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining\/ , pp.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining\/ , pp

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.352350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eeb857b3-1d91-4518-8f23-db3ae983cff1 · outbound

This paper cites Mechanical Systems and Signal Processing 84 , 34--53.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network Mechanical Systems and Signal Processing 84 , 34--53

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.340677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 70f56585-db3c-44e7-afb1-f058f61f6cbc · outbound

This paper cites ACM Transactions on Graphics (TOG) 37 (4), 1--15.

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network ACM Transactions on Graphics (TOG) 37 (4), 1--15

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:12:33.328935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers