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Gaussian Processes

CTA is a testing environment for online heterogenous task assignment approaches which involve representation of worker-task pairs as noisy functions.

"n" dimensional input with "m" objectives example of a Pareto front with the BOSS code. In these examples we reproduce the pareto front as produced by mathlab in the link below "https://www.mathworks.com/help/gads/pareto-front-for-two-objectives.html" For 3D inputs and 3 objectives, we try to reproduce these results The difference in these methods is that here we calculate the pareto front using GP functions with an RBF kernel.

Data simulations for Gaussian Process Classification of data from sensors attached to a hypothetical machine.

Source Code for Gabler et al. "Bayesian Optimization with Unknown Constraints in Graphical Skill-Models for Compliant Manipulation Tasks Using an Industrial Robot", Frontiers in Robotics and AI, 2022

Learning in the Wild with Incremental Skeptical Gaussian Processes

This is a pilot project for a future iteration of The Alice Challenge: remote control of an ultracold atoms experiment by experts and citizen scientist. Scientific paper available here: https://www.pnas.org/content/115/48/E11231

Miscellaneous Machine Learning Example Code for sci-kit learn, refactored to PEP8 style

Scalable Gaussian processes in TensorFlow