An implementation of Neural ODEs in PyTorch.
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Updated
Aug 25, 2022 - Python
An implementation of Neural ODEs in PyTorch.
PINEURODEs is a repository collecting CMS group research work on the application of neural (stochastic/ordinary) differential equations and physically-informed neural networks to model complex multiscale systems.
Accompanying code for the paper "Amortized reparametrization: efficient and scalable variational inference for latent SDEs
On the forward invariance of Neural ODEs: performance guarantees for policy learning
Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (NeurIPS 2022)
This repo is the official implementation for the series of works on (Path-dependent) Neural Jump ODEs.
Neural Ordinary Differential Equations for Reinforcement Learning
Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
Python tools for non-intrusive reduced order modeling
[TKDE 2022] The official PyTorch implementation of the paper "Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs".
Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)
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