Alternatives and similar repositories for tfdiffeq:

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

• EmilienDupont / augmented-neural-odes
  Pytorch implementation of Augmented Neural ODEs
  ☆537Updated 2 years ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆278Updated 3 years ago
• greydanus / hamiltonian-nn
  Code for our paper "Hamiltonian Neural Networks"
  ☆459Updated 3 years ago
• MilesCranmer / lagrangian_nns
  Lagrangian Neural Networks
  ☆483Updated 8 months ago
• msurtsukov / neural-ode
  Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
  ☆737Updated last year
• patrick-kidger / torchcde
  Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
  ☆433Updated last year
• amirgholami / anode
  [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
  ☆103Updated 4 years ago
• rtqichen / ffjord
  code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".
  ☆637Updated 4 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆124Updated 5 months ago
• Rachnog / Neural-ODE-Experiments
  This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data
  ☆197Updated 5 years ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆89Updated 3 years ago
• luckystarufo / multiscale_HiTS
  ☆72Updated 4 years ago
• patrick-kidger / sympytorch
  Turning SymPy expressions into PyTorch modules.
  ☆146Updated last year
• mfinzi / constrained-hamiltonian-neural-networks
  ☆105Updated 3 years ago
• llSourcell / Neural_Differential_Equations
  This is the code for "Neural DIfferential Equations" By Siraj Raval on Youtube
  ☆245Updated 6 years ago
• patrick-kidger / NeuralCDE
  Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
  ☆645Updated 2 years ago
• mandubian / neural-ode
  Neural Ordinary Differential Equation
  ☆101Updated 6 years ago
• boschresearch / torchphysics
  ☆428Updated 3 months ago
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆127Updated 6 months ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆227Updated 3 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆437Updated 6 months ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆222Updated 3 months ago
• DiffEqML / torchdyn
  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
  ☆1,456Updated 10 months ago
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆120Updated 3 years ago
• YuliaRubanova / latent_ode
  Code for "Latent ODEs for Irregularly-Sampled Time Series" paper
  ☆549Updated 4 years ago
• analysiscenter / pydens
  PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
  ☆306Updated last year
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆229Updated 4 years ago
• JSeam2 / Neural-Ordinary-Differential-Equations
  Sample implementation of Neural Ordinary Differential Equations
  ☆259Updated 6 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago