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🤿 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"
Jupyter Notebooks Tutorials on Gaussian Processes
Actually Sparse Variational Gaussian Processes implemented in GPlow
📈 Implementation of the Graph Gaussian Process using GPflow and TensorFlow 2
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
Study of Gaussian Process (GP) local and global approximations, and application of the sparse GP approximation, combining both the global and local approaches.
LaTeX code for my PhD thesis.
Towards GPflow 1.0