Alternatives and similar repositories for phd-thesis

Users that are interested in phd-thesis are comparing it to the libraries listed below

• jamesrobertlloyd / gp-structure-search
  ☆233Updated 7 years ago
• jamesrobertlloyd / gpss-research
  Kernel structure discovery research code - likely to be unstable
  ☆190Updated 9 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆233Updated 4 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• SheffieldML / GPmat
  Matlab implementations of Gaussian processes and other machine learning tools.
  ☆139Updated 7 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆32Updated 8 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated 10 months ago
• SheffieldML / notebook
  Collection of jupyter notebooks for demonstrating software.
  ☆167Updated 2 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆105Updated 7 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated 10 months ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆188Updated 4 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆125Updated 7 months ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆114Updated 11 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆48Updated 4 years ago
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆269Updated 5 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆66Updated 2 years ago
• sods / paramz
  Parameterization Framework for parameterized model creation and handling.
  ☆49Updated 4 months ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆214Updated 6 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• AaltoML / SDE
  Example codes for the book Applied Stochastic Differential Equations
  ☆192Updated 3 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆230Updated last week
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 6 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 3 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• SheffieldML / multigp
  Multiple output Gaussian processes in MATLAB including the latent force model.
  ☆51Updated 9 years ago
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆232Updated last year