Alternatives and similar repositories for A-United-Framework-to-Integrate-Physics-into-Gaussian-Processes

Users that are interested in A-United-Framework-to-Integrate-Physics-into-Gaussian-Processes are comparing it to the libraries listed below

• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆63Updated this week
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 7 years ago
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆74Updated 2 years ago
• Giodiro / NystromKoopman
  ☆11Updated last year
• sdascoli / odeformer
  ☆67Updated last year
• sydney-machine-learning / Bayesianneuralnetworks-MCMC-tutorial
  Bayesian neural networks via MCMC: tutorial
  ☆58Updated last year
• hegdepashupati / gaussian-process-odes
  Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes
  ☆13Updated 3 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆62Updated last year
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆77Updated this week
• hvarfner / vanilla_bo_in_highdim
  ☆30Updated 8 months ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆25Updated 9 years ago
• josephbakarji / deep-delay-autoencoder
  Discovers high dimensional models from 1D data using deep delay autoencoders
  ☆37Updated 2 years ago
• arbabiha / StochasticModelingwData
  Data-driven modeling of chaotic systems in the form of SDEs and nonlinear observation maps
  ☆19Updated 5 years ago
• ETH-WindMil / JSD-SBI
  A toolbox for Sequential Bayesian Inference in uncertain nonlinear dynamic systems.
  ☆14Updated last year
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• clegaard / deep_learning_for_dynamical_systems
  ☆89Updated 2 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆48Updated last year
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆12Updated 3 years ago
• NickGeneva / blog-code
  Code and files related to random side projects
  ☆21Updated 3 years ago
• ae-foster / pyro
  Deep universal probabilistic programming with Python and PyTorch
  ☆12Updated 5 years ago
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆29Updated 4 months ago
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 6 months ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆55Updated last year
• htlambley / functional_autoencoders
  Autoencoders in Function Space: Resolution-invariant autoencoders for functional data based on the functional variational autoencoder (FV…
  ☆27Updated last week
• MachineLearningLifeScience / hdbo_benchmark
  Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"
  ☆14Updated 8 months ago
• kpchamp / MultiscaleDiscovery
  ☆30Updated 7 years ago
• benavoli / SkewGP
  Skew Gaussian Processes by Alessio Benavoli, Dario Azzimonti and Dario Piga
  ☆16Updated 2 months ago