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
  ☆42Updated 6 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆115Updated 12 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
• zi-w / Max-value-Entropy-Search
  Max-value Entropy Search for Efficient Bayesian Optimization
  ☆78Updated 3 years ago
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆43Updated 4 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆53Updated 5 years ago
• automl / pybnn
  Bayesian neural network package
  ☆152Updated 4 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• PredictiveScienceLab / uq-course
  Introduction to Uncertainty Quantification
  ☆254Updated 3 years ago
• QUVA-Lab / COMBO
  ☆50Updated last year
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆94Updated 7 years ago
• rubinxin / CoCaBO_code
  Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)
  ☆51Updated 6 years ago
• cambridge-mlg / sghmc_dgp
  ☆29Updated 6 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• maziarraissi / ParametricGP-in-Matlab
  Parametric Gaussian Process Regression for Big Data (Matlab Version)
  ☆24Updated 7 years ago
• baptistar / BOCS
  Bayesian Optimization of Combinatorial Structures
  ☆97Updated 6 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆151Updated 6 years ago
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 5 years ago
• shib0li / DNN-MFBO
  Multi-fidelity Bayesian Optimization via Deep Neural Nets
  ☆33Updated 4 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• markm541374 / gpbo
  gpbo
  ☆25Updated 4 years ago
• kirthevasank / gp-parallel-ts
  Parallelised Thompson Sampling in GPs for Bayesian Optimisation
  ☆36Updated 8 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆26Updated 6 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 3 years ago
• zi-w / Ensemble-Bayesian-Optimization
  Code repository for Ensemble Bayesian Optimization
  ☆54Updated 6 years ago