Gaussian processes in TensorFlow

Bayesian Optimization using GPflow

Deep convolutional gaussian processes.

Non-stationary spectral mixture kernels implemented in GPflow

🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0

Dataset and code for "Uncertainty-Informed Deep Transfer Learning of PFAS Toxicity"

Gaussian-Processes Surrogate Optimisation in python

Library for Deep Gaussian Processes based on GPflow

Jupyter Notebooks Tutorials on Gaussian Processes

📈 Implementation of the Graph Gaussian Process using GPflow and TensorFlow 2

Actually Sparse Variational Gaussian Processes implemented in GPlow

Interactive Gaussian Processes

Methods for estimating time-varying functional connectivity (TVFC)

Distributed surrogate-assisted evolutionary methods for multi-objective optimization of high-dimensional dynamical systems

Sparse Heteroscedastic Gaussian Processes

Subset of Data Variational Inference for Deep Gaussian Process Model

Mode-constrained model-based-reinforcement learning in TensorFlow/GPflow

LaTeX code for my PhD thesis.

Study of Gaussian Process (GP) local and global approximations, and application of the sparse GP approximation, combining both the global and local approaches.

Gaussian processes in TensorFlow