a-norcliffe / sonodeLinks
Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
☆60Updated 11 months ago
Alternatives and similar repositories for sonode
Users that are interested in sonode are comparing it to the libraries listed below
Sorting:
- Official code for the ICLR 2021 paper Neural ODE Processes☆74Updated 3 years ago
- Refining continuous-in-depth neural networks☆42Updated 3 years ago
- ☆48Updated last year
- Experiments for Neural Flows paper☆97Updated 3 years ago
- This repository contains code released by DiffEqML Research☆90Updated 3 years ago
- Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domain…☆104Updated 3 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆129Updated last year
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆54Updated 3 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 2 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Regularized Neural ODEs (RNODE)☆85Updated 4 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆56Updated 4 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆62Updated 4 years ago
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆120Updated 2 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.☆80Updated 4 months ago
- Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series☆118Updated 2 years ago
- Neural Graph Differential Equations (Neural GDEs)☆204Updated 4 years ago
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]☆15Updated 4 years ago
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆53Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆40Updated 2 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆55Updated last year
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆53Updated 5 years ago
- ☆38Updated 5 years ago