Identifiability and Asymptotics in Learning Homogeneous Linear ODE
Systems from Discrete Observations

Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations

12 October 2022

Yuanyuan Wang

Papers citing "Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations"

8 / 8 papers shown

Title
On Robustness of Neural Ordinary Differential Equations Hanshu Yan Jiawei Du Vincent Y. F. Tan Jiashi Feng OOD 72 141 0 12 Oct 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 214 2,108 0 08 Oct 2019
Data Driven Governing Equations Approximation Using Deep Neural Networks Tong Qin Kailiang Wu D. Xiu PINN 62 272 0 13 Nov 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 368 5,081 0 19 Jun 2018
From Deterministic ODEs to Dynamic Structural Causal Models Paul Kishan Rubenstein Stephan Bongers Bernhard Schölkopf Joris M. Mooij 65 54 0 29 Aug 2016
From Ordinary Differential Equations to Structural Causal Models: the deterministic case Joris Mooij Dominik Janzing Bernhard Schölkopf 106 104 0 09 Aug 2014
Causal interpretation of stochastic differential equations Alexander Sokol N. Hansen CML 134 50 0 31 Mar 2013
Sieve estimation of constant and time-varying coefficients in nonlinear ordinary differential equation models by considering both numerical error and measurement error Hongqi Xue Hongyu Miao Hulin Wu 78 120 0 20 Oct 2010