DiffEqML / torchdynLinks
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
☆1,506Updated last year
Alternatives and similar repositories for torchdyn
Users that are interested in torchdyn are comparing it to the libraries listed below
Sorting:
- A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…☆1,448Updated 10 months ago
- Differentiable SDE solvers with GPU support and efficient sensitivity analysis.☆1,660Updated 6 months ago
- Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations☆765Updated last year
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,693Updated 3 weeks ago
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆440Updated last year
- Normalizing flows in PyTorch☆929Updated 6 months ago
- Constrained optimization toolkit for PyTorch☆687Updated 3 years ago
- Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)☆659Updated 2 years ago
- Pytorch implementation of Augmented Neural ODEs☆542Updated 2 years ago
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆647Updated 4 years ago
- Code for "Discovering Symbolic Models from Deep Learning with Inductive Biases"☆757Updated last year
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆451Updated 10 months ago
- Code for our paper "Hamiltonian Neural Networks"☆475Updated 4 years ago
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆281Updated 3 years ago
- Awesome resources on normalizing flows.☆1,541Updated last week
- Code for "Latent ODEs for Irregularly-Sampled Time Series" paper☆560Updated 4 years ago
- Lagrangian Neural Networks☆504Updated last year
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆6,042Updated 3 months ago
- Hardware accelerated, batchable and differentiable optimizers in JAX.☆979Updated 3 months ago
- PyTorch implementation of normalizing flow models☆855Updated 10 months ago
- Laplace approximations for Deep Learning.☆514Updated 2 months ago
- KErnel OPerationS, on CPUs and GPUs, with autodiff and without memory overflows☆1,107Updated this week
- A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…☆748Updated last week
- Normalizing flows in PyTorch☆396Updated last month
- Differentiable convex optimization layers☆1,958Updated last month
- Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.☆614Updated last week
- [NeurIPS'19] Deep Equilibrium Models☆753Updated 3 years ago
- Computations and statistics on manifolds with geometric structures.☆1,378Updated last month
- OSS library that implements deep learning methods for partial differential equations and much more☆444Updated 2 months ago
- A PyTorch implementation of L-BFGS.☆606Updated 2 years ago