LaTeX code for my PhD thesis.
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Updated
Apr 19, 2024 - TeX
LaTeX code for my PhD thesis.
Mode-constrained model-based-reinforcement learning in TensorFlow/GPflow
Gaussian processes in TensorFlow
Towards GPflow 1.0
Subset of Data Variational Inference for Deep Gaussian Process Model
Implementation of the COGP model
Implements AT-GP from Cao et. al. 2010 in GPflow
Study of Gaussian Process (GP) local and global approximations, and application of the sparse GP approximation, combining both the global and local approaches.
Methods for estimating time-varying functional connectivity (TVFC)
Gaussian-Processes Surrogate Optimisation in python
Interactive Gaussian Processes
Sparse Heteroscedastic Gaussian Processes
📈 Implementation of the Graph Gaussian Process using GPflow and TensorFlow 2
Actually Sparse Variational Gaussian Processes implemented in GPlow
Dataset and code for "Uncertainty-Informed Deep Transfer Learning of PFAS Toxicity"
Jupyter Notebooks Tutorials on Gaussian Processes
Distributed surrogate-assisted evolutionary methods for multi-objective optimization of high-dimensional dynamical systems
Non-stationary spectral mixture kernels implemented in GPflow
Library for Deep Gaussian Processes based on GPflow
🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
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