neural-ode

Closed-form Continuous-time Neural Networks

Code for the paper "Learning Differential Equations that are Easy to Solve"

A parallel ODE solver for PyTorch

Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support

Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

Official PyTorch implementation for the paper Minimizing Trajectory Curvature of ODE-based Generative Models, ICML 2023

Regularized Neural ODEs (RNODE)

Implementation of (2018) Neural Ordinary Differential Equations on Keras

Code for our RSS'21 paper: "Hamiltonian-based Neural ODE Networks on the SE(3) Manifold For Dynamics Learning and Control"

APDTFlow is a modern and extensible forecasting framework for time series data that leverages advanced techniques including neural ordinary differential equations (Neural ODEs), transformer-based components, and probabilistic modeling. Its modular design allows researchers and practitioners to experiment with multiple forecasting models and easily

[NeurIPS 2025] E-MoFlow: Learning Egomotion and Optical Flow from Event Data via Implicit Regularization

LT-OCF: Learnable-Time ODE-based Collaborative Filtering, CIKM'21

[ICASSP 2025 Oral] ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images

Official code release for the paper: Grow with the Flow: 4D Reconstruction of Growing Plants with Gaussian Flow Fields

CVPR2021 paper "Learning Parallel Dense Correspondence from Spatio-Temporal Descriptorsfor Efficient and Robust 4D Reconstruction"

Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561

NDE: Climate Modeling with Neural Diffusion Equation, ICDM'21

The official PyTorch implementation of "Learning to Simulate Daily Activities via Modeling Dynamic Human Needs" (WWW'23)

Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"

[𝗜𝗖𝗔𝗦𝗦𝗣 𝟮𝟬𝟮𝟱 𝗢𝗿𝗮𝗹] ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images