DiffEqML / diffeqml-researchLinks
This repository contains code released by DiffEqML Research
☆90Updated 3 years ago
Alternatives and similar repositories for diffeqml-research
Users that are interested in diffeqml-research are comparing it to the libraries listed below
Sorting:
- ☆109Updated 4 years ago
- Refining continuous-in-depth neural networks☆40Updated 3 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 8 months ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆56Updated 4 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- ☆101Updated 4 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 3 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 3 years ago
- Convex potential flows☆83Updated 3 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.☆77Updated 2 months ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆128Updated 9 months ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- ☆47Updated last year
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆46Updated last year
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆281Updated 3 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- ☆45Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆32Updated 3 years ago
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆52Updated 2 years ago
- Monotone operator equilibrium networks☆52Updated 5 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- Port-Hamiltonian Approach to Neural Network Training☆24Updated 5 years ago
- Consistent Koopman Autoencoders☆74Updated 2 years ago
- Package for CGD and ACGD optimizers☆20Updated 2 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆104Updated 4 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆118Updated 4 years ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago