Alternatives and similar repositories for gaussian-process-odes

Users that are interested in gaussian-process-odes are comparing it to the libraries listed below

• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆63Updated this week
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• NickHunt-Smith / MCMC-diffusion
  A Metropolis-Hastings MCMC sampler accelerated via diffusion models
  ☆16Updated last year
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆55Updated last year
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆62Updated last year
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 7 years ago
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆56Updated 3 years ago
• wjmaddox / online_gp
  Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
  ☆64Updated 4 years ago
• plugyawn / gp-zoo
  A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…
  ☆14Updated 2 years ago
• ghliu / DeepGSB
  Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral
  ☆52Updated 3 years ago
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 6 months ago
• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆15Updated 3 years ago
• alonfnt / pcax
  Differentiable Principal Component Analysis (PCA) implementation in JAX
  ☆29Updated 6 months ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆38Updated 3 years ago
• OxfordML / bayesquad
  Library for Bayesian Quadrature
  ☆32Updated 6 years ago
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆14Updated 2 years ago
• gd-vae / gd-vae
  Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This …
  ☆34Updated last month
• pnnl / NeuralDAEs
  Learning Neural Differential Algebraic Equations via Operator Splitting
  ☆20Updated 3 months ago
• Benjamin-Walker / log-neural-cdes
  Code for "Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference" (ICML 2024)
  ☆23Updated last week
• darioizzo / neurostability
  The code used for the paper "On the stability analysis of optimal state feedbacks as represented by deep neural models"
  ☆16Updated 5 years ago
• DecodEPFL / HamiltonianNet
  PyTorch implementation of Hamiltonian deep neural networks.
  ☆21Updated 3 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆116Updated 3 weeks ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆112Updated 4 years ago
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆12Updated last year
• MachineLearningLifeScience / hdbo_benchmark
  Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"
  ☆14Updated 8 months ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆47Updated 4 years ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆91Updated 3 years ago
• pnkraemer / matfree
  Matrix-free linear algebra in JAX.
  ☆145Updated last month
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆55Updated 3 years ago