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.
  ☆65Updated this week
• wjmaddox / online_gp
  Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
  ☆64Updated 4 years ago
• Benjamin-Walker / log-neural-cdes
  Code for "Log Neural Controlled Differential Equations" (ICML 2024) and "Structured Linear CDEs" (NeurIPS 2025, Spotlight)
  ☆28Updated last week
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆31Updated 2 years ago
• NickHunt-Smith / MCMC-diffusion
  A Metropolis-Hastings MCMC sampler accelerated via diffusion models
  ☆16Updated last year
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆74Updated 5 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
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 8 months ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆65Updated last year
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆57Updated 3 years ago
• MachineLearningLifeScience / hdbo_benchmark
  Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"
  ☆15Updated 10 months ago
• balintmate / boltzmann-interpolations
  ☆10Updated 2 years ago
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆14Updated 2 years ago
• htlambley / functional_autoencoders
  Autoencoders in Function Space: Resolution-invariant autoencoders for functional data based on the functional variational autoencoder (FV…
  ☆31Updated 3 weeks ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆47Updated 4 years ago
• ghliu / DeepGSB
  Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral
  ☆52Updated 3 years ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆40Updated 3 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆56Updated last year
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• Giodiro / NystromKoopman
  ☆11Updated last year
• take-koshizuka / NLSB
  ☆21Updated 10 months ago
• pnnl / NeuralDAEs
  Learning Neural Differential Algebraic Equations via Operator Splitting
  ☆21Updated 5 months ago
• OxfordML / bayesquad
  Library for Bayesian Quadrature
  ☆32Updated 6 years ago
• fidero / gp-derivative
  Example code to speed up GP inference with gradients for high-dimensional inputs.
  ☆14Updated 4 years ago
• alonfnt / pcax
  Differentiable Principal Component Analysis (PCA) implementation in JAX
  ☆30Updated 8 months ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆27Updated 7 years ago
• NoemieJaquier / MaternGaBO
  This repository contains the code for the paper "Geometry-aware Bayesian Optimization in Roboticsusing Riemannian Matérn Kernels" (CoRL'2…
  ☆21Updated 2 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆48Updated 2 years ago
• DenisBless / variational_sampling_methods
  [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".
  ☆41Updated last year