gpflow

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

Gaussian-Processes Surrogate Optimisation in python

Library for Deep Gaussian Processes based on GPflow

Interactive Gaussian Processes

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

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

Sparse Heteroscedastic Gaussian Processes

Jupyter Notebooks Tutorials on Gaussian Processes

Subset of Data Variational Inference for Deep Gaussian Process Model

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

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

Implementation of the COGP model

Implements AT-GP from Cao et. al. 2010 in GPflow

Gaussian processes in TensorFlow

Towards GPflow 1.0