Alternatives and similar repositories for gpytorch:

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

• maziarraissi / TutorialGP
  Tutorial on Gaussian Processes
  ☆62Updated 4 years ago
• Xiao-dong-Wang / Multifidelity-GP
  Multi-fidelity Gaussian Process
  ☆25Updated 4 years ago
• jwangjie / Gaussian-Process-Regression-Tutorial
  An Intuitive Tutorial to Gaussian Processes Regression
  ☆570Updated 11 months ago
• ablancha / gpsearch
  Bayesian optimization and active learning with likelihood-weighted acquisition functions
  ☆16Updated 7 months ago
• XuhuiM / Multi-Fidelity-DNNs-PINNs
  ☆35Updated last year
• HildoBijl / GPRT
  Gaussian Process Regression Techniques - The source code corresponding to the Ph.D. thesis.
  ☆72Updated 7 years ago
• paraklas / NARGP
  Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.
  ☆59Updated 8 years ago
• rmojgani / LPINNs
  To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…
  ☆44Updated 2 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆48Updated 3 years ago
• shib0li / DNN-MFBO
  Multi-fidelity Bayesian Optimization via Deep Neural Nets
  ☆29Updated 4 years ago
• ymchen0 / torchEnKF
  Code for the paper "Auto differentiable Ensemble Kalman Filters" (https://arxiv.org/abs/2107.07687), accepted for publication in SIAM Jou…
  ☆29Updated 2 years ago
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆70Updated 3 years ago
• ShuaiGuo16 / Surrogate_Optimization
  A step-by-step guide for surrogate optimization using Gaussian Process surrogate model
  ☆29Updated 4 years ago
• MarcusHA94 / structural-dynamics-pinns
  Research/development of physics-informed neural networks for dynamic systems
  ☆16Updated last month
• opaliss / dmd_autoencoder
  Enhancing Dynamic Mode Decomposition using Autoencoder Networks.
  ☆29Updated 3 years ago
• xdfeng7370 / Multi-fidelity-neural-network-
  ☆35Updated last year
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆91Updated last year
• ContiPaolo / EKF-SINDy
  Empowering extended Kalman filter (EKF) with Sparse Identification of Nonlinear Dynamics (SINDy)
  ☆45Updated this week
• sydney-machine-learning / Bayesianneuralnetworks-MCMC-tutorial
  Bayesian neural networks via MCMC: tutorial
  ☆43Updated 2 months ago
• sjvrijn / mf2
  Collection of Multi-Fidelity benchmark functions
  ☆27Updated 4 months ago
• Bigpig4396 / Incremental-Gaussian-Process-Regression-IGPR
  ☆15Updated 3 years ago
• zzhang222 / Bayesian-PINN-Pytorch
  ☆14Updated 2 years ago
• urban-fasel / EnsembleSINDy
  ☆19Updated 3 years ago
• nguyenkhoa0209 / pinns_tutorial
  Tutorials for Physics-Informed Neural Networks
  ☆36Updated 7 months ago
• paraklas / GPTutorial
  A hands-on tutorial on supervised learning with Gaussian processes
  ☆36Updated 5 years ago
• cfl-minds / drl_shape_optimization
  Deep reinforcement learning to perform shape optimization
  ☆60Updated 3 years ago
• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆166Updated 9 months ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆42Updated 3 years ago
• jjdabr / BPINN-Wildfire
  Implementation of Dabrowski et. al., "Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wi…
  ☆17Updated 9 months ago