How to Learn and Generalize From Three Minutes of Data:
Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential
Equations

How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations

10 June 2023

Ufuk Topcu

Papers citing "How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations"

17 / 17 papers shown

Title
Multi-Robot Collaboration through Reinforcement Learning and Abstract Simulation Adam Labiosa Josiah P. Hanna 54 0 0 07 Mar 2025
Improving the Noise Estimation of Latent Neural Stochastic Differential Equations Linus Heck Maximilian Gelbrecht Michael T. Schaub Niklas Boers DiffM 35 0 0 23 Dec 2024
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 82 1 0 15 Dec 2024
Reference-Free Formula Drift with Reinforcement Learning: From Driving Data to Tire Energy-Inspired, Real-World Policies Franck Djeumou Michael Thompson Makoto Suminaka John Subosits 16 1 0 28 Oct 2024
Zero-Shot Transfer of Neural ODEs Tyler Ingebrand Adam J. Thorpe Ufuk Topcu 36 4 0 14 May 2024
A Method to Improve the Performance of Reinforcement Learning Based on the Y Operator for a Class of Stochastic Differential Equation-Based Child-Mother Systems Cheng Yin Yi Chen 17 0 0 07 Nov 2023
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization Jihwan Jeong Xiaoyu Wang Michael Gimelfarb Hyunwoo J. Kim Baher Abdulhai Scott Sanner OffRL 82 11 0 07 Oct 2022
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble Gaon An Seungyong Moon Jang-Hyun Kim Hyun Oh Song OffRL 105 265 0 04 Oct 2021
OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation J. Wong Viktor Makoviychuk Anima Anandkumar Yuke Zhu 34 11 0 02 Oct 2021
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu PINN AI4CE 47 69 0 14 Sep 2021
COMBO: Conservative Offline Model-Based Policy Optimization Tianhe Yu Aviral Kumar Rafael Rafailov Aravind Rajeswaran Sergey Levine Chelsea Finn OffRL 222 419 0 16 Feb 2021
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty 52 35 0 12 Feb 2021
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates Lingkai Kong Jimeng Sun Chao Zhang UQCV 50 103 0 24 Aug 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 343 1,968 0 04 May 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 139 425 0 10 Mar 2020
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 152 221 0 29 Sep 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,683 0 05 Dec 2016