google-research / torchsdeLinks
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
☆1,701Updated last year
Alternatives and similar repositories for torchsde
Users that are interested in torchsde are comparing it to the libraries listed below
Sorting:
- A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods☆1,552Updated last year
- A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…☆1,515Updated last year
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,888Updated this week
- Normalizing flows in PyTorch☆989Updated last year
- Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)☆697Updated 3 years ago
- Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations☆795Updated last year
- Fast and Easy Infinite Neural Networks in Python☆2,370Updated last year
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆465Updated 4 months ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆464Updated last year
- Differentiable convex optimization layers☆2,046Updated this week
- Hardware accelerated, batchable and differentiable optimizers in JAX.☆1,022Updated last month
- Constrained optimization toolkit for PyTorch☆706Updated 6 months ago
- Computations and statistics on manifolds with geometric structures.☆1,449Updated last week
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆664Updated 5 years ago
- Awesome resources on normalizing flows.☆1,605Updated 6 months ago
- Pytorch implementation of Augmented Neural ODEs☆555Updated 2 years ago
- Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.☆2,597Updated this week
- Laplace approximations for Deep Learning.☆532Updated 9 months ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆6,324Updated 9 months ago
- A highly efficient implementation of Gaussian Processes in PyTorch☆3,821Updated last week
- PyTorch implementation of normalizing flow models☆928Updated last year
- Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/☆2,757Updated this week
- Code for "Latent ODEs for Irregularly-Sampled Time Series" paper☆583Updated 5 years ago
- A simple probabilistic programming language.☆706Updated 3 weeks ago
- Code for "Discovering Symbolic Models from Deep Learning with Inductive Biases"☆773Updated 2 years ago
- Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.☆698Updated this week
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆287Updated 4 years ago
- BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.☆1,005Updated last month
- KErnel OPerationS, on CPUs and GPUs, with autodiff and without memory overflows☆1,155Updated 3 months ago
- Optax is a gradient processing and optimization library for JAX.☆2,169Updated this week