Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data

22 February 2024

Papers citing "Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data"

31 / 31 papers shown

Title
Trajectory Flow Matching with Applications to Clinical Time Series Modeling Xi Zhang Yuan Pu Yuki Kawamura Andrew Loza Yoshua Bengio Dennis L. Shung Alexander Tong OOD AI4TS MedIm 70 7 0 28 Oct 2024
Domain Adaptation under Missingness Shift Helen Zhou Sivaraman Balakrishnan Zachary Chase Lipton 44 9 0 03 Nov 2022
$Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient$ Langevin dynamics based algorithm e-TH $\varepsilon$ O POULA for stochastic optimization problems with discontinuous stochastic gradient Dongjae Lim Ariel Neufeld Sotirios Sabanis Ying Zhang 44 7 0 24 Oct 2022
EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting Sheo Yon Jhin Jaehoon Lee Minju Jo Seung-Uk Kook Jinsung Jeon Jihyeon Hyeong Jayoung Kim Noseong Park AI4TS 58 20 0 19 Apr 2022
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization John Miller Rohan Taori Aditi Raghunathan Shiori Sagawa Pang Wei Koh Vaishaal Shankar Percy Liang Y. Carmon Ludwig Schmidt OODD OOD 65 274 0 09 Jul 2021
Neural Controlled Differential Equations for Online Prediction Tasks James Morrill Patrick Kidger Lingyi Yang Terry Lyons AI4TS 78 42 0 21 Jun 2021
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks Dong-Young Lim Sotirios Sabanis 69 12 0 28 May 2021
Efficient and Accurate Gradients for Neural SDEs Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 59 66 0 27 May 2021
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning Aodong Li Alex Boyd Padhraic Smyth Stephan Mandt 31 24 0 15 Dec 2020
Neural Rough Differential Equations for Long Time Series James Morrill C. Salvi Patrick Kidger James Foster Terry Lyons AI4TS 66 132 0 17 Sep 2020
Learning Long-Term Dependencies in Irregularly-Sampled Time Series Mathias Lechner Ramin Hasani AI4TS 45 128 0 08 Jun 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 90 470 0 18 May 2020
The Effect of Natural Distribution Shift on Question Answering Models John Miller K. Krauth Benjamin Recht Ludwig Schmidt OOD 82 144 0 29 Apr 2020
Time series classification for varying length series Chang Wei Tan F. Petitjean Eamonn Keogh Geoffrey I. Webb AI4TS 44 31 0 10 Oct 2019
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks Mahyar Fazlyab Alexander Robey Hamed Hassani M. Morari George J. Pappas 87 456 0 12 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 159 1,688 0 06 Jun 2019
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series E. Brouwer Jaak Simm Adam Arany Yves Moreau SyDa CML AI4TS 91 295 0 29 May 2019
Neural Jump Stochastic Differential Equations Junteng Jia Austin R. Benson BDL 57 225 0 24 May 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit Belinda Tzen Maxim Raginsky DiffM 154 209 0 23 May 2019
Augmented Neural ODEs Emilien Dupont Arnaud Doucet Yee Whye Teh BDL 127 626 0 02 Apr 2019
The UEA multivariate time series classification archive, 2018 A. Bagnall Hoang Anh Dau Jason Lines Michael Flynn J. Large A. Bostrom Paul Southam Eamonn Keogh AI4TS 144 426 0 31 Oct 2018
The UCR Time Series Archive Hoang Anh Dau A. Bagnall Kaveh Kamgar Chin-Chia Michael Yeh Yan Zhu Shaghayegh Gharghabi C. Ratanamahatana Eamonn Keogh 52 828 0 17 Oct 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 361 5,081 0 19 Jun 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 75 527 0 28 May 2018
DeepMind Control Suite Yuval Tassa Yotam Doron Alistair Muldal Tom Erez Yazhe Li ... A. Abdolmaleki J. Merel Andrew Lefrancq Timothy Lillicrap Martin Riedmiller ELM LM&Ro BDL 127 1,133 0 02 Jan 2018
Ray: A Distributed Framework for Emerging AI Applications Philipp Moritz Robert Nishihara Stephanie Wang Alexey Tumanov Richard Liaw ... Melih Elibol Zongheng Yang William Paul Michael I. Jordan Ion Stoica GNN 89 1,256 0 16 Dec 2017
Discrete Event, Continuous Time RNNs Michael C. Mozer Denis Kazakov Robert V. Lindsey 51 55 0 11 Oct 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 70 521 0 13 Feb 2017
Recurrent Neural Networks for Multivariate Time Series with Missing Values Zhengping Che S. Purushotham Kyunghyun Cho David Sontag Yan Liu AI4TS 305 1,934 0 06 Jun 2016
Doctor AI: Predicting Clinical Events via Recurrent Neural Networks Edward Choi M. T. Bahadori A. Schuetz Walter F. Stewart Jimeng Sun 139 1,100 0 18 Nov 2015
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 523 12,692 0 11 Dec 2014