Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics

9 May 2021

Papers citing "Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics"

7 / 7 papers shown

Title
When are dynamical systems learned from time series data statistically accurate? Jeongjin Park Nicole Yang Nisha Chandramoorthy AI4TS 34 4 0 09 Nov 2024
PosDiffNet: Positional Neural Diffusion for Point Cloud Registration in a Large Field of View with Perturbations Rui She Sijie Wang Qiyu Kang Kai Zhao Yang Song Wee Peng Tay Tianyu Geng Xingchao Jian DiffM 3DPC 34 2 0 06 Jan 2024
Faster Training of Neural ODEs Using Gauß-Legendre Quadrature Alexander Norcliffe M. Deisenroth 23 3 0 21 Aug 2023
Trainability, Expressivity and Interpretability in Gated Neural ODEs T. Kim T. Can K. Krishnamurthy AI4CE 32 4 0 12 Jul 2023
Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed! Avik Pal Alan Edelman Chris Rackauckas 19 3 0 03 Mar 2023
torchode: A Parallel ODE Solver for PyTorch Marten Lienen Stephan Günnemann LRM 19 11 0 22 Oct 2022
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu AI4TS 14 17 0 14 Jan 2022