Paper Citation Record · LEDGER

The HydroGym Reinforcement Learning Platform for Fluid Dynamics

As of 13 August 2026, this Paper Citation Record lists 100 of 250 outbound references and 4 inbound Pith citation observations for arXiv:2512.17534.

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

pith.paper-citation-record.v1
2512.17534 v2

Coverage vector

measured 100 of 250 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T15:17:06.858095Z

measured 104 of 104 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T09:03:31.868534Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:14:25.864392Z

Reference resolution

100 of 250 outbound references displayed

verified exact1
verified fuzzy0
unresolved99
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9fecdfe6-b993-4522-a8c0-d5fbc3e851c4 · outbound

This paper cites Marusic, D.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Marusic, D

Reference 1

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Observation f2db149f-8416-4a56-b8a1-e7eaf3b916fe · outbound

This paper cites Mäteling, M.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Mäteling, M

Reference 2

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Observation fc7fdb3c-9712-4b57-a5a8-9b770c84c0ad · outbound

This paper cites A review of turbulent skin-friction drag reduction by near-wall transverse forcing.Prog.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics A review of turbulent skin-friction drag reduction by near-wall transverse forcing.Prog

Reference 3

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Observation 441e889c-352e-4fdf-8de9-3d7311b13cbf · outbound

This paper cites an unresolved cited work.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

Reference 4

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Observation 39bf67f9-125f-4026-ad14-9a3b1d106cf8 · outbound

This paper cites Cooperative wind farm control with deep reinforcement learning and knowledge-assisted learning.IEEE Transactions on Industrial Informatics, 16(11):6912–6921, 2020.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Cooperative wind farm control with deep reinforcement learning and knowledge-assisted learning.IEEE Transactions on Industrial Informatics, 16(11):6912–6921, 2020

Reference 5

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Observation b6f43300-2797-4597-b22c-84698504aee5 · outbound

This paper cites Dalili, A.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Dalili, A

Reference 6

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Observation 52ed99ea-731a-4d16-a6f7-45c59cd50618 · outbound

This paper cites P Chamorro, REA Arndt, and Fotis Sotiropou- los.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics P Chamorro, REA Arndt, and Fotis Sotiropou- los

Reference 7

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Observation c2b2d60f-dac7-4f83-aee0-e3e5520a7d34 · outbound

This paper cites Kaltenbach, and P.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Kaltenbach, and P

Reference 8

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Observation 5e556ed3-baf7-40c5-a03b-10f210e0682f · outbound

This paper cites an unresolved cited work.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

Reference 9

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Observation b959e630-1015-491d-a31e-18cef3c713ca · outbound

This paper cites Brunton, B.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Brunton, B

Reference 10

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Observation 6fb95bc3-f77e-4858-8a5d-6d686e30f709 · outbound

This paper cites Koumoutsakos.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Koumoutsakos

Reference 11

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Observation 51a2bd65-65b6-4238-a48d-685f30d5eff1 · outbound

This paper cites Jumper, R.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Jumper, R

Reference 12

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Observation f6023e04-c30d-40e5-954f-ef8ff0c818c2 · outbound

This paper cites Degrave, F.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Degrave, F

Reference 13

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Observation 101d6308-f201-450c-b25d-a2b17a256899 · outbound

This paper cites Kochkov, J.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Kochkov, J

Reference 14

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Observation e2477764-74bb-4801-8bd5-e07364f0940d · outbound

This paper cites Rabault, Arnau Miró, Bernat Font, O.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Rabault, Arnau Miró, Bernat Font, O

Reference 15

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Observation bb66d372-4efc-4a49-b50c-fa6b48af3c56 · outbound

This paper cites an unresolved cited work.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

Reference 16

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Observation c822769a-c5ac-48f8-b26d-6239bb6c242e · outbound

This paper cites SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning

Reference 17

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Observation 3314fc7a-d570-4d2e-9e1b-eebb14029aa3 · outbound

This paper cites Vinyals, I.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Vinyals, I

Reference 18

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Observation a396ce9e-2687-4efe-bc13-e07124d0024b · outbound

This paper cites Chatzimanolakis, P.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Chatzimanolakis, P

Reference 19

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Observation 8a716013-2310-47f7-97e8-319dcd0e7f14 · outbound

This paper cites an unresolved cited work.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

Reference 20

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Observation 1d377ba4-fecb-400a-a077-6cc876fe0dc1 · outbound

This paper cites Bhola, S.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Bhola, S

Reference 21

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Observation 1b89b4d9-8783-4dea-8b5c-a48c6d5f06a2 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Imagenet: A large-scale hierarchical image database

Reference 22

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Observation 6fe4d59a-65dd-44a2-973e-34c53b6f757d · outbound

This paper cites Todorov, T.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Todorov, T

Reference 23

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Observation aefb4420-477e-4ddd-a10c-ec22b39492d2 · outbound

This paper cites m-AIA, 2024.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics m-AIA, 2024

Reference 24

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Observation a0a86c01-ffd7-4886-9103-fdee7f16558e · outbound

This paper cites Bradbury, R.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Bradbury, R

Reference 25

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Observation 6b8bf0e2-d53e-4965-9972-9ad4f107ef88 · outbound

This paper cites Ham, Paul H.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Ham, Paul H

Reference 26

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Observation d9f81cab-8180-4215-9a49-47f63f87206c · outbound

This paper cites Gymnasium: A Standard Interface for Reinforcement Learning Environments.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 27

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Observation bdffce43-e758-4134-801b-10777291052e · outbound

This paper cites Drake: Model-based design and verification for robotics, 2019.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Drake: Model-based design and verification for robotics, 2019

Reference 28

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Observation 15ec320e-410a-4ffb-ab3a-a99b418fbbd0 · outbound

This paper cites Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning

Reference 29

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Observation a822b1aa-32b9-4406-8ca6-5f2c0a887249 · outbound

This paper cites Mittal, C.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Mittal, C

Reference 30

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Observation 753b59ae-6f5a-4601-958f-97343b620feb · outbound

This paper cites Suárez, F.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Suárez, F

Reference 32

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Observation 863b0f91-a334-4a81-af97-e2f7bc7e7fc7 · outbound

This paper cites Proximal Policy Optimization Algorithms.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Proximal Policy Optimization Algorithms

Reference 33

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Observation 99141337-069f-459a-a7a5-5b497099fe8a · outbound

This paper cites Continuous control with deep reinforcement learning.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Continuous control with deep reinforcement learning

Reference 34

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

Reference 35

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Observation 20d9dc24-e7c9-4eca-99d6-ec7b0a7178e1 · outbound

This paper cites Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fab- ritiis, and Vincent Moens.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fab- ritiis, and Vincent Moens

Reference 36

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Observation d4b3f6a2-b72a-4b84-bd2e-260c065460fd · outbound

This paper cites Huang, R.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Huang, R

Reference 37

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

Reference 38

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Observation dd766bdc-d84c-4c22-a16e-d27478321498 · outbound

This paper cites Accelerated Policy Learning with Parallel Differentiable Simulation.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Accelerated Policy Learning with Parallel Differentiable Simulation

Reference 39

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Observation 04a3b738-f989-4644-a2a6-e9c733e74aba · outbound

This paper cites Direct numerical simulation of turbulent channel flow up to re= 590.Phys.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Direct numerical simulation of turbulent channel flow up to re= 590.Phys

Reference 40

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

Reference 41

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This paper cites Blanchard and T.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Blanchard and T

Reference 42

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This paper cites W Rowley, D.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics W Rowley, D

Reference 43

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics R Williams, C

Reference 44

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Bagheri, J

Reference 45

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Colonius and D

Reference 46

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Sipp and P

Reference 47

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics List, L.-W

Reference 49

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Koehler, S

Reference 50

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This paper cites Learning to Control PDEs with Differentiable Physics.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Learning to Control PDEs with Differentiable Physics

Reference 51

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Maulik, K

Reference 52

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Duraisamy, G

Reference 53

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Brandt, and Dan S Henningson

Reference 55

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Improving turbulence control through explainable deep learning

Reference 56

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Cremades, S

Reference 57

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Lozano-Durán and H

Reference 58

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Martínez-Sánchez, G

Reference 59

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Lagemann, B

Reference 60

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Cranmer, Alvaro Sanchez-Gonzalez, Rui Battaglia, P .and Xu, Kyle Cranmer, D

Reference 61

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

Reference 63

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics OpenAI Gym

Reference 64

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Vinuesa and S

Reference 65

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Observation d80812c7-5ba6-474f-8198-3150962b2a74 · outbound

This paper cites Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation

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Observation 4b80c33d-e0e6-4b46-b8d7-4de5d4b3f1ed · outbound

This paper cites On the choice of physical constraints in arti- ficial neural networks for predicting flow fields.Fu- ture Generation Computer Systems, 161:361–375, 2024.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics On the choice of physical constraints in arti- ficial neural networks for predicting flow fields.Fu- ture Generation Computer Systems, 161:361–375, 2024

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Observation 00bbd447-a0d4-4a40-b5e4-ff48bcfa4d48 · outbound

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Large-eddy simulation of turbulent flow over the drivaer fastback vehicle model.Journal of Wind En- gineering and Industrial Aerodynamics, 186:123–138, 2019

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Observation dbde3e65-6c99-4051-9d59-4dbba2ba6d0f · outbound

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Lagemann, S.L Brunton, W

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Observation fe33e432-b3c4-4be2-b377-d16cd7698b4e · outbound

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Impact of reynolds number on the drag reduction mechanism of span- wise travelling surface waves.Flow, Turbulence and Combustion, 113(1):27–40, 2024

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Observation 10e71d8b-b3e5-4a27-8562-3e1d99666485 · outbound

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Rabault, M

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Observation abc4ea37-da9e-4bf9-8795-441daceef1d3 · outbound

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Deep reinforcement learning con- trol of cylinder flow using rotary oscillations at low reynolds number.Energies, 13(22):5920, 2020

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Observation 3cdcbd0b-23ea-4be7-961a-2ed465b081ea · outbound

This paper cites an unresolved cited work.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

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Observation df4f0494-e71b-4c06-b4e4-316181324dd7 · outbound

This paper cites Rabault and Alexander Kuhnle.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Rabault and Alexander Kuhnle

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Observation f55b4a84-5a54-4d1f-a951-eb31cb99eb9c · outbound

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Rabault, and B

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Observation 3b575f5a-3d88-4a09-b9ee-714127595523 · outbound

This paper cites an unresolved cited work.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

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Observation b897985a-2aeb-4478-a56e-fd8ea669d8cd · outbound

This paper cites an unresolved cited work.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Unresolved cited work

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Observation 4f58e114-d5f7-48bc-9ac0-f9d32a8c5caa · outbound

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Rabault, R

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Observation 2ae130d0-3ac3-4525-b571-da27bd48c0b6 · outbound

This paper cites Deep reinforcement transfer learning for active flow control of a 3D square cylinder under state dimension mismatch.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Deep reinforcement transfer learning for active flow control of a 3D square cylinder under state dimension mismatch

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Observation 095039e9-b37b-4d14-b90f-d9fcc3981ce0 · outbound

This paper cites Active flow control for bluff body drag reduction using reinforcement learning with partial measurements.Journal of Fluid Mechanics, 981:A17, 2024.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Active flow control for bluff body drag reduction using reinforcement learning with partial measurements.Journal of Fluid Mechanics, 981:A17, 2024

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Observation ab256cb8-21ab-4a6c-9f7b-8d2ceb0bf6e0 · outbound

This paper cites Robust and adaptive deep reinforcement learning for enhancing flow control around a square cylinder with varying reynolds numbers.Physics of Fluids, 36(5), 2024.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Robust and adaptive deep reinforcement learning for enhancing flow control around a square cylinder with varying reynolds numbers.Physics of Fluids, 36(5), 2024

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Observation 8dc80cb5-519d-4eec-8419-0a6a681e0dae · outbound

This paper cites Rabault, Alexander Kuhnle, Hassan Ghraieb, Aurélien Larcher, and Elie Hachem.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Rabault, Alexander Kuhnle, Hassan Ghraieb, Aurélien Larcher, and Elie Hachem

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Observation 44a39e10-544c-4102-9dc5-4ca826597205 · outbound

This paper cites Rüttgers, M.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Rüttgers, M

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Observation b0aaf8a0-b006-455c-9363-4fcfd1c281b9 · outbound

This paper cites Aerodynamic optimization of airfoil based on deep reinforcement learning.Physics of Fluids, 35(3), 2023.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Aerodynamic optimization of airfoil based on deep reinforcement learning.Physics of Fluids, 35(3), 2023

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Observation 5eda7688-b3e7-4cc9-88af-f54458e75228 · outbound

This paper cites A reinforce- ment learning approach to airfoil shape optimiza- tion.Scientific Reports, 13(1):9753, 2023.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics A reinforce- ment learning approach to airfoil shape optimiza- tion.Scientific Reports, 13(1):9753, 2023

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Observation d2fd3034-a7c4-4518-b5a9-eab8714d25a9 · outbound

This paper cites Enhancing vehicle aerodynamics with deep reinforcement learning in voxelised models.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Enhancing vehicle aerodynamics with deep reinforcement learning in voxelised models

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Observation c7a33fd0-fb9f-4d2b-b141-c9a67aa87c7c · outbound

This paper cites Aerodynamics-guided machine learning for design optimization of electric vehicles.Commu- nications Engineering, 3(1):174, 2024.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Aerodynamics-guided machine learning for design optimization of electric vehicles.Commu- nications Engineering, 3(1):174, 2024

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Observation 76c6142a-6d43-467f-a1f8-af80282a0952 · outbound

This paper cites Deep-reinforcement-learning-based hull form opti- mization method for stealth submarine design.In- ternational Journal of Naval Architecture and Ocean Engineering, 16:100595, 2024.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Deep-reinforcement-learning-based hull form opti- mization method for stealth submarine design.In- ternational Journal of Naval Architecture and Ocean Engineering, 16:100595, 2024

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Observation fc819cae-cdc9-4ea1-a5d7-0f7858f151f2 · outbound

This paper cites Oh, M.-J.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Oh, M.-J

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Observation 46332453-22e2-4e45-adea-3ec303369c09 · outbound

This paper cites Xiang, H.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Xiang, H

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Observation 26cf1153-7ef0-45aa-99ce-fb3d8bbeb4fd · outbound

This paper cites Closed- loop flow separation control using the deep Q net- work over airfoil.AIAA Journal, 58(10):4260–4270, 2020.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Closed- loop flow separation control using the deep Q net- work over airfoil.AIAA Journal, 58(10):4260–4270, 2020

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Observation 5d4fb302-bd3c-4fce-b373-3bdd2e20d119 · outbound

This paper cites Garcia, A.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Garcia, A

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Observation 0e8eed68-6f66-4251-a197-c23ceaa8541f · outbound

This paper cites Guastoni, J.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Guastoni, J

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Observation 7f5442cc-5da2-424a-be96-490b03986202 · outbound

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Turbulence control for drag reduction through deep reinforcement learning.Phys

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Reinforcement-learning-based control of turbulent channel flows at high Reynolds numbers.J

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This paper cites Reinforcement learning of con- trol strategies for reducing skin friction drag in a 16 fully developed turbulent channel flow.J.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Reinforcement learning of con- trol strategies for reducing skin friction drag in a 16 fully developed turbulent channel flow.J

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Observation 2464e12b-62be-41df-920d-e914bbcc315b · outbound

This paper cites Novati, S.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Novati, S

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Observation a8e4ad50-f8a1-48d0-8a53-833d2046f596 · outbound

This paper cites Verma, G.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Verma, G

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Source-reported events for the cited work

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Observation d67b1f7a-4ff7-4728-9f30-2b35f5530b4c · outbound

This paper cites Reinforcement learning of a multi-link swimmer at low Reynolds numbers.Physics of Fluids, 35(3), 2023.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Reinforcement learning of a multi-link swimmer at low Reynolds numbers.Physics of Fluids, 35(3), 2023

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The HydroGym Reinforcement Learning Platform for Fluid Dynamics Chemotactic navi- gation in robotic swimmers via reset-free hierarchi- cal reinforcement learning.Nat

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Observation afe5d50d-8ffb-4b71-a241-c3039117d5a2 · outbound

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Pith citing papers

Observation 8f7ac81b-ebaa-4290-8b52-27b4cb57f1e0 · inbound

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Observation 935d9859-40d7-41e3-b6c0-bc88eefca31e · inbound

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 33ce9bce-6cbe-4356-aa86-d8ab984c9e8f · inbound

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Weak Dominant Balance for Robust Identification of Dynamically Consistent Fluid Flow Structure The HydroGym Reinforcement Learning Platform for Fluid Dynamics

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c79c3f35-949f-4952-8b05-938edc226cfd · inbound

Microcosmos: Reimagining Artificial Life for the GPU Era cites this paper.

Microcosmos: Reimagining Artificial Life for the GPU Era The HydroGym Reinforcement Learning Platform for Fluid Dynamics

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