DiffEqML / diffeqml-research
This repository contains code released by DiffEqML Research
☆85Updated 2 years ago
Alternatives and similar repositories for diffeqml-research:
Users that are interested in diffeqml-research are comparing it to the libraries listed below
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆57Updated 4 months ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆54Updated 3 years ago
- ☆104Updated 3 years ago
- ☆45Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- Convex potential flows☆82Updated 3 years ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆70Updated 2 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆126Updated 5 months ago
- ☆44Updated 4 years ago
- ☆99Updated 4 years ago
- Nonparametric Differential Equation Modeling☆53Updated 11 months ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- [NeurIPS'19] Deep Equilibrium Models Jax Implementation☆39Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Monotone operator equilibrium networks☆51Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆115Updated 3 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆115Updated last year
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆49Updated last year
- Experiments for Neural Flows paper☆93Updated 3 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆103Updated 4 years ago
- Riemannian Convex Potential Maps☆67Updated last year
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆58Updated 4 years ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆42Updated last year
- Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.☆74Updated last month