jamesrobertlloyd / gp-structure-search

Related projects ⓘ

Alternatives and complementary repositories for gp-structure-search

• jamesrobertlloyd / gpss-research
  Kernel structure discovery research code - likely to be unstable
  ☆189Updated 9 years ago
• duvenaud / phd-thesis
  I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth
  ☆178Updated 10 years ago
• GPflow / GPflowOpt
  Bayesian Optimization using GPflow
  ☆270Updated 3 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆232Updated 3 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆213Updated 5 years ago
• SheffieldML / notebook
  Collection of jupyter notebooks for demonstrating software.
  ☆165Updated last year
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆147Updated 5 years ago
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆262Updated 4 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆247Updated 3 months ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆113Updated 11 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆120Updated last month
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 6 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆241Updated 2 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆90Updated 3 years ago
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆134Updated 3 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆51Updated 4 years ago
• vlad17 / runlmc
  Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.
  ☆36Updated last year
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆31Updated 7 years ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆185Updated 4 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆79Updated 4 months ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆147Updated 3 months ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆83Updated 3 years ago
• clinicalml / structuredinference
  Structured Inference Networks for Nonlinear State Space Models
  ☆265Updated 7 years ago
• ColCarroll / minimc
  Just a little MCMC
  ☆217Updated 4 months ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆107Updated 7 years ago
• mfouesneau / NUTS
  python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011
  ☆126Updated 3 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆109Updated 2 years ago
• elfi-dev / elfi
  ELFI - Engine for Likelihood-Free Inference
  ☆267Updated 4 months ago
• HIPS / Probabilistic-Backpropagation
  Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
  ☆192Updated 5 years ago