Closed-form Continuous-time Neural Networks
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Updated
Jul 5, 2024 - Python
Closed-form Continuous-time Neural Networks
Code for the paper "Learning Differential Equations that are Easy to Solve"
Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
Regularized Neural ODEs (RNODE)
Official PyTorch implementation for the paper Minimizing Trajectory Curvature of ODE-based Generative Models, ICML 2023
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"
LT-OCF: Learnable-Time ODE-based Collaborative Filtering, CIKM'21
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
Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"
The official PyTorch implementation of "Learning to Simulate Daily Activities via Modeling Dynamic Human Needs" (WWW'23)
A toolbox for learning with neural ODEs.
Repository for notes, projects and snippets on NODEs. Includes results after training CNN based networks with different methods on MNIST, CIFAR-10, CelebA and CatsAndDogs datasets accordingly.
This is a repo for Neural ODE and CDE forecasters.
Code for "Time-Reversal Symmetric ODE Network (NeurIPS 2020)"
Fit time-series data with a Neural Differential Equation!
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