Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise

5 June 2019

Sanjiv Kumar

Papers citing "Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise"

39 / 39 papers shown

Title
Robust Asymmetric Heterogeneous Federated Learning with Corrupted Clients Xiuwen Fang Mang Ye Bo Du FedML 79 1 0 12 Mar 2025
Learning to Decouple Complex Systems Zihan Zhou Tianshu Yu BDL 79 4 0 17 Feb 2025
Universal randomised signatures for generative time series modelling Francesca Biagini Lukas Gonon Niklas Walter 42 4 0 14 Jun 2024
Continuous-Time Digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver Hegan Chen Jichang Yang Jia Chen Songqi Wang Shaocong Wang ... Han Wang Dashan Shang Qi Liu Kwang-Ting Cheng Ming Liu 52 0 0 12 Jun 2024
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems Xin Li Jingdong Zhang Qunxi Zhu Chengli Zhao Xue Zhang Xiaojun Duan Wei Lin 63 3 0 19 May 2024
Neural Controlled Differential Equations with Quantum Hidden Evolutions Lingyi Yang Zhen Shao 34 0 0 30 Apr 2024
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data YongKyung Oh Dongyoung Lim Sungil Kim AI4TS 45 13 0 22 Feb 2024
Continuously Evolving Graph Neural Controlled Differential Equations for Traffic Forecasting Jiajia Wu Ling Chen AI4TS 29 2 0 26 Jan 2024
Operator-learning-inspired Modeling of Neural Ordinary Differential Equations Woojin Cho Seunghyeon Cho Hyundong Jin Jinsung Jeon Kookjin Lee Sanghyun Hong Dongeun Lee Jonghyun Choi Noseong Park AI4TS AI4CE 23 2 0 16 Dec 2023
Faster Training of Neural ODEs Using Gauß-Legendre Quadrature Alexander Norcliffe M. Deisenroth 33 3 0 21 Aug 2023
Neural Delay Differential Equations: System Reconstruction and Image Classification Qunxi Zhu Yao Guo Wei Lin 25 32 0 11 Apr 2023
Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed! Avik Pal Alan Edelman Chris Rackauckas 42 3 0 03 Mar 2023
TIDE: Time Derivative Diffusion for Deep Learning on Graphs M. Behmanesh Maximilian Krahn M. Ovsjanikov DiffM GNN 29 9 0 05 Dec 2022
E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations Jongwan Kim Dongjin Lee Byunggook Na Seongsik Park Jeonghee Jo Sung-Hoon Yoon 42 0 0 15 Jun 2022
Standalone Neural ODEs with Sensitivity Analysis Rym Jaroudi Lukáš Malý Gabriel Eilertsen B. Johansson Jonas Unger George Baravdish 23 0 0 27 May 2022
Path Development Network with Finite-dimensional Lie Group Representation Han Lou Siran Li Hao Ni 23 7 0 02 Apr 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed Shian Du Yihong Luo Wei Chen Jian Xu Delu Zeng 37 7 0 19 Mar 2022
Learning Stochastic Dynamics with Statistics-Informed Neural Network Yuanran Zhu Yunhao Tang Changho Kim 19 18 0 24 Feb 2022
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 34 3 0 25 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 33 93 0 02 Nov 2021
Federated Learning as a Mean-Field Game Arash Mehrjou FedML MLT AI4CE 19 3 0 08 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 46 65 0 02 Jul 2021
GRAND: Graph Neural Diffusion B. Chamberlain J. Rowbottom Maria I. Gorinova Stefan Webb Emanuele Rossi M. Bronstein GNN 54 254 0 21 Jun 2021
Efficient and Accurate Gradients for Neural SDEs Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 29 61 0 27 May 2021
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics Avik Pal Yingbo Ma Viral B. Shah Chris Rackauckas 28 36 0 09 May 2021
Deep limits and cut-off phenomena for neural networks B. Avelin A. Karlsson AI4CE 43 2 0 21 Apr 2021
Meta-Solver for Neural Ordinary Differential Equations Julia Gusak A. Katrutsa Talgat Daulbaev A. Cichocki Ivan Oseledets 16 2 0 15 Mar 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li David Duvenaud BDL UQCV 27 46 0 12 Feb 2021
Self-Progressing Robust Training Minhao Cheng Pin-Yu Chen Sijia Liu Shiyu Chang Cho-Jui Hsieh Payel Das AAML VLM 29 9 0 22 Dec 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 Sep 2020
A Differential Game Theoretic Neural Optimizer for Training Residual Networks Guan-Horng Liu T. Chen Evangelos A. Theodorou 24 2 0 17 Jul 2020
STEER: Simple Temporal Regularization For Neural ODEs Arna Ghosh Harkirat Singh Behl Emilien Dupont Philip Torr Vinay P. Namboodiri BDL AI4TS 27 74 0 18 Jun 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 27 451 0 18 May 2020
Stochasticity in Neural ODEs: An Empirical Study V. Oganesyan Alexandra Volokhova Dmitry Vetrov BDL 30 20 0 22 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics Alexander Tong Jessie Huang Guy Wolf David van Dijk Smita Krishnaswamy 29 163 0 09 Feb 2020
Scalable Gradients for Stochastic Differential Equations Xuechen Li Ting-Kam Leonard Wong Ricky T. Q. Chen David Duvenaud 17 312 0 05 Jan 2020
On Robustness of Neural Ordinary Differential Equations Hanshu Yan Jiawei Du Vincent Y. F. Tan Jiashi Feng OOD 24 138 0 12 Oct 2019
Bayesian Learning-Based Adaptive Control for Safety Critical Systems David D. Fan Jennifer Nguyen Rohan Thakker Nikhilesh Alatur Ali-akbar Agha-mohammadi Evangelos A. Theodorou BDL 36 84 0 05 Oct 2019