Abstract: Achieving precise trajectory tracking for autonomous mobile robots in complex and dynamic environments poses a demanding challenge. In this study, we propose an innovative approach for the ...
Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...
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