Alternatives and similar repositories for Deep-Gaussian-Process

Users that are interested in Deep-Gaussian-Process are comparing it to the libraries listed below

• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated last year
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆48Updated 2 years 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
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 5 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 10 months ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 4 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated last year
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆67Updated 5 months ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• idelbrid / Randomly-Projected-Additive-GPs
  Code for Randomly Projected Additive Gaussian Processes
  ☆25Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆24Updated 9 years ago
• oxcsml / kerpy
  python code for kernel methods
  ☆38Updated 6 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆32Updated 3 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• VirgiAgl / DAG-GP
  Code for the paper Multi-task Causal Learning with Gaussian Processes (https://arxiv.org/pdf/2009.12821.pdf)
  ☆12Updated 4 years ago
• markvdw / GPflow-inter-domain
  Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
  ☆13Updated 7 years ago
• thjashin / solvegp
  Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)
  ☆22Updated 4 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago