Learning to Control PDEs with Differentiable Physics

21 January 2020

Papers citing "Learning to Control PDEs with Differentiable Physics"

20 / 120 papers shown

Title
Neural Particle Image Velocimetry N. Stulov Michael Chertkov 9 7 0 28 Jan 2021
DiffPD: Differentiable Projective Dynamics Tao Du Kui Wu Pingchuan Ma Sebastien Wah Andrew Spielberg Daniela Rus Wojciech Matusik 18 94 0 15 Jan 2021
How to Train Your Differentiable Filter Alina Kloss Georg Martius Jeannette Bohg 36 46 0 28 Dec 2020
Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D Nils Wandel Michael Weinmann Reinhard Klein AI4CE 26 50 0 22 Dec 2020
On The Verification of Neural ODEs with Stochastic Guarantees Sophie Gruenbacher Ramin Hasani Mathias Lechner J. Cyranka S. Smolka Radu Grosu 66 31 0 16 Dec 2020
DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation Jungeun Kim Kookjin Lee Dongeun Lee Sheo Yon Jin Noseong Park PINN AI4CE 12 77 0 04 Dec 2020
Scalable Differentiable Physics for Learning and Control Yi-Ling Qiao Junbang Liang V. Koltun Ming Lin PINN AI4CE 22 118 0 04 Jul 2020
ADD: Analytically Differentiable Dynamics for Multi-Body Systems with Frictional Contact Moritz Geilinger D. Hahn Jonas Zehnder M. Bacher B. Thomaszewski Stelian Coros AI4CE 14 41 0 02 Jul 2020
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers Kiwon Um R. Brand Yun Fei Fei Philipp Holl N. Thürey AI4CE 19 256 0 30 Jun 2020
Learning Physical Constraints with Neural Projections Shuqi Yang Xingzhe He Bo Zhu 3DV AI4CE 25 25 0 23 Jun 2020
Neural Ordinary Differential Equation Control of Dynamics on Graphs Thomas Asikis Lucas Böttcher Nino Antulov-Fantulin 25 42 0 17 Jun 2020
Learning Incompressible Fluid Dynamics from Scratch -- Towards Fast, Differentiable Fluid Models that Generalize Nils Wandel Michael Weinmann Reinhard Klein AI4CE 11 8 0 15 Jun 2020
Liquid Time-constant Networks Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus Radu Grosu AI4TS AI4CE 14 215 0 08 Jun 2020
Learning Long-Term Dependencies in Irregularly-Sampled Time Series Mathias Lechner Ramin Hasani AI4TS 12 127 0 08 Jun 2020
Neural Vortex Method: from Finite Lagrangian Particles to Infinite Dimensional Eulerian Dynamics S. Xiong Xingzhe He Yunjin Tong Yitong Deng Bo Zhu 14 11 0 07 Jun 2020
Lagrangian Neural Style Transfer for Fluids Byungsoo Kim Vinicius Azevedo Markus Gross B. Solenthaler 28 37 0 02 May 2020
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 100 49 0 27 Feb 2020
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 51 1,046 0 21 Feb 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 43 2,009 0 08 Oct 2019
SPNets: Differentiable Fluid Dynamics for Deep Neural Networks Connor Schenck D. Fox PINN 3DPC AI4CE 172 161 0 15 Jun 2018