Python package 'dgpsi' for deep and linked Gaussian process emulations
-
Updated
Mar 17, 2026 - Python
#
deep-gaussian-processes
Here are 11 public repositories matching this topic...
🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
-
Updated
Feb 11, 2024 - Python
Library for Deep Gaussian Processes based on GPflow
-
Updated
Mar 31, 2020 - Python
Reference implementation of Thin and Deep Gaussian Processes (NeurIPS 2023)
-
Updated
Nov 25, 2024 - Python
Code for the NeurIPS 2021 paper "Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features"
-
Updated
May 25, 2022 - Python
Deep Gaussian processes based on GPyTorch — doubly-stochastic variational DGPs: modular SVGP layers, a configurable deep-GP builder, ELBO training, and calibrated prediction
deep-neural-networks pytorch gaussian-processes bayesian-neural-networks deep-gaussian-processes gpytorch
-
Updated
Aug 31, 2026 - Python
Codes for paper "Stochastic Deep Gaussian Processes over Graphs"
-
Updated
Aug 15, 2020 - Python
A C++ implementation of Deep Gaussian Process with Stochastic Imputation
-
Updated
Jan 17, 2022 - C++
PyTorch implementation of shallow and deep nonparametric convolutions for Gaussian processes
-
Updated
Feb 15, 2023 - Python
Evaluating Deep Gaussian processes
deep-learning bayesian bayesian-inference gaussian-processes pyro nuts deep-kernel-learning deep-gaussian-processes gpytorch sk2torch bayesian-gaussian-processes
-
Updated
Mar 10, 2024 - Jupyter Notebook
R interface to 'dgpsi' for deep and linked Gaussian process emulations
-
Updated
Jul 18, 2026 - R
Add this topic to your repo
To associate your repository with the deep-gaussian-processes topic, visit your repo's landing page and select "manage topics."