Alternatives and similar repositories for NIPS2017:

Users that are interested in NIPS2017 are comparing it to the libraries listed below

• aminnayebi / HesBO
  The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces
  ☆41Updated 5 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆44Updated 5 years ago
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆41Updated 3 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• QUVA-Lab / COMBO
  ☆50Updated 8 months ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 7 years ago
• zi-w / Max-value-Entropy-Search
  Max-value Entropy Search for Efficient Bayesian Optimization
  ☆73Updated 3 years ago
• maziarraissi / ParametricGP-in-Matlab
  Parametric Gaussian Process Regression for Big Data (Matlab Version)
  ☆24Updated 6 years ago
• martinjankowiak / saasbo
  SAASBO: a package for high-dimensional bayesian optimization
  ☆42Updated 3 years ago
• kpchamp / MultiscaleDiscovery
  ☆28Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 6 years ago
• shib0li / DNN-MFBO
  Multi-fidelity Bayesian Optimization via Deep Neural Nets
  ☆30Updated 4 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 4 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• philipk01 / Optimization_and_Sampling_for_Bayesian_Inference
  Adaptive MCMC and CMA-ES Python code
  ☆14Updated 5 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 5 years ago
• kd383 / GPML_SLD
  Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)
  ☆18Updated 7 years ago
• kirthevasank / gp-parallel-ts
  Parallelised Thompson Sampling in GPs for Bayesian Optimisation
  ☆36Updated 7 years ago
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 5 years ago
• zi-w / Structural-Kernel-Learning-for-HDBBO
  Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
  ☆14Updated 6 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• amkatrutsa / DeepPDE
  Deep Learning application to the partial differential equations
  ☆30Updated 6 years ago
• juliusberner / Deep-Multilevel-Kolmogorov-PDE-Solver
  Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation
  ☆12Updated 3 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆30Updated 9 months ago
• kirthevasank / add-gp-bandits
  Additive Gaussian Process Bandits - version 1.0
  ☆27Updated 8 years ago
• paraklas / GPTutorial
  A hands-on tutorial on supervised learning with Gaussian processes
  ☆36Updated 5 years ago
• luckystarufo / multiscale_HiTS
  ☆72Updated 4 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 8 months ago