Alternatives and similar repositories for torchsde

Users that are interested in torchsde are comparing it to the libraries listed below

• DiffEqML / torchdyn
  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
  ☆1,544Updated last year
• Zymrael / awesome-neural-ode
  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…
  ☆1,500Updated last year
• patrick-kidger / diffrax
  Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
  ☆1,855Updated this week
• patrick-kidger / NeuralCDE
  Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
  ☆692Updated 3 years ago
• msurtsukov / neural-ode
  Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
  ☆788Updated last year
• patrick-kidger / torchcde
  Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
  ☆463Updated 3 months ago
• bayesiains / nflows
  Normalizing flows in PyTorch
  ☆979Updated 11 months ago
• EmilienDupont / augmented-neural-odes
  Pytorch implementation of Augmented Neural ODEs
  ☆551Updated 2 years ago
• google / neural-tangents
  Fast and Easy Infinite Neural Networks in Python
  ☆2,365Updated last year
• google / jaxopt
  Hardware accelerated, batchable and differentiable optimizers in JAX.
  ☆1,007Updated this week
• cvxpy / cvxpylayers
  Differentiable convex optimization layers
  ☆2,029Updated this week
• rtqichen / ffjord
  code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".
  ☆662Updated 5 years ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆286Updated 4 years ago
• lezcano / geotorch
  Constrained optimization toolkit for PyTorch
  ☆705Updated 4 months ago
• janosh / awesome-normalizing-flows
  Awesome resources on normalizing flows.
  ☆1,596Updated 5 months ago
• YuliaRubanova / latent_ode
  Code for "Latent ODEs for Irregularly-Sampled Time Series" paper
  ☆576Updated 5 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆463Updated last year
• google-deepmind / optax
  Optax is a gradient processing and optimization library for JAX.
  ☆2,121Updated this week
• MilesCranmer / symbolic_deep_learning
  Code for "Discovering Symbolic Models from Deep Learning with Inductive Biases"
  ☆769Updated 2 years ago
• VincentStimper / normalizing-flows
  PyTorch implementation of normalizing flow models
  ☆917Updated last year
• greydanus / hamiltonian-nn
  Code for our paper "Hamiltonian Neural Networks"
  ☆496Updated 4 years ago
• google-deepmind / jraph
  A Graph Neural Network Library in Jax
  ☆1,457Updated last year
• karpathy / pytorch-normalizing-flows
  Normalizing flows in PyTorch. Current intended use is education not production.
  ☆905Updated 5 years ago
• patrick-kidger / equinox
  Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
  ☆2,715Updated 2 weeks ago
• pyro-ppl / numpyro
  Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
  ☆2,571Updated this week
• rtqichen / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆6,271Updated 8 months ago
• blackjax-devs / blackjax
  BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.
  ☆982Updated 2 weeks ago
• getkeops / keops
  KErnel OPerationS, on CPUs and GPUs, with autodiff and without memory overflows
  ☆1,149Updated last month
• google / edward2
  A simple probabilistic programming language.
  ☆703Updated 3 months ago
• probabilists / zuko
  Normalizing flows in PyTorch
  ☆435Updated 3 weeks ago