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Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints

16 June 2023

Papers citing "Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints"

26 / 26 papers shown

Title
Predicting Ordinary Differential Equations with Transformers Soren Becker M. Klein Alexander Neitz Giambattista Parascandolo Niki Kilbertus 76 17 0 24 Jul 2023
Sparsity in Continuous-Depth Neural Networks H. Aliee Till Richter Mikhail Solonin I. Ibarra Fabian J. Theis Niki Kilbertus 72 11 0 26 Oct 2022
NODE IK: Solving Inverse Kinematics with Neural Ordinary Differential Equations for Path Planning Suhan Park M. Schwartz Jaeheung Park 33 7 0 01 Sep 2022
Differentiable Programming for Earth System Modeling Maximilian Gelbrecht Alistair J R White S. Bathiany Niklas Boers 59 19 0 29 Aug 2022
Matching Normalizing Flows and Probability Paths on Manifolds Heli Ben-Hamu Samuel N. Cohen Joey Bose Brandon Amos Aditya Grover Maximilian Nickel Ricky T. Q. Chen Y. Lipman 96 42 0 11 Jul 2022
projUNN: efficient method for training deep networks with unitary matrices B. Kiani Randall Balestriero Yann LeCun S. Lloyd 70 32 0 10 Mar 2022
Deconstructing the Inductive Biases of Hamiltonian Neural Networks Nate Gruver Marc Finzi Samuel Stanton A. Wilson AI4CE 50 41 0 10 Feb 2022
Moser Flow: Divergence-based Generative Modeling on Manifolds N. Rozen Aditya Grover Maximilian Nickel Y. Lipman DRL AI4CE 75 60 0 18 Aug 2021
Beyond Predictions in Neural ODEs: Identification and Interventions H. Aliee Fabian J. Theis Niki Kilbertus CML 101 25 0 23 Jun 2021
Universal Approximation Property of Neural Ordinary Differential Equations Takeshi Teshima Koichi Tojo Masahiro Ikeda Isao Ishikawa Kenta Oono 70 40 0 04 Dec 2020
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints Marc Finzi Ke Alexander Wang A. Wilson AI4CE 73 129 0 26 Oct 2020
Learning Differential Equations that are Easy to Solve Jacob Kelly J. Bettencourt Matthew J. Johnson David Duvenaud 86 116 0 09 Jul 2020
Riemannian Continuous Normalizing Flows Emile Mathieu Maximilian Nickel AI4CE 96 126 0 18 Jun 2020
Neural Manifold Ordinary Differential Equations Aaron Lou Derek Lim Isay Katsman Leo Huang Qingxuan Jiang Ser-Nam Lim Christopher De Sa BDL AI4CE 74 81 0 18 Jun 2020
On Second Order Behaviour in Augmented Neural ODEs Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lio 73 94 0 12 Jun 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 173 437 0 10 Mar 2020
Normalizing Flows on Tori and Spheres Danilo Jimenez Rezende George Papamakarios S. Racanière M. S. Albergo G. Kanwar P. Shanahan Kyle Cranmer TPM 84 157 0 06 Feb 2020
Universal Differential Equations for Scientific Machine Learning Christopher Rackauckas Yingbo Ma Julius Martensen Collin Warner K. Zubov R. Supekar Dominic J. Skinner Ali Ramadhan Alan Edelman AI4CE 91 597 0 13 Jan 2020
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN 88 271 0 26 Sep 2019
Approximation Capabilities of Neural ODEs and Invertible Residual Networks Han Zhang Xi Gao Jacob Unterman Tom Arodz 74 99 0 30 Jul 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 118 899 0 04 Jun 2019
Augmented Neural ODEs Emilien Dupont Arnaud Doucet Yee Whye Teh BDL 150 632 0 02 Apr 2019
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group Mario Lezcano Casado David Martínez-Rubio 50 200 0 24 Jan 2019
Fashionable Modelling with Flux Mike Innes Elliot Saba Keno Fischer Dhairya Gandhi Marco Concetto Rudilosso Neethu Mariya Joy Tejan Karmali Avik Pal Viral B. Shah AI4CE 79 164 0 01 Nov 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 429 5,157 0 19 Jun 2018
Unitary Evolution Recurrent Neural Networks Martín Arjovsky Amar Shah Yoshua Bengio ODL 75 771 0 20 Nov 2015