José Miguel Hernández Lobato

José Miguel Hernández Lobato, a machine learning lecturer at the University of Cambridge, shares insights on the fusion of Bayesian learning and deep learning in molecular design. He discusses innovative methods for predicting chemical reactions and explores the challenges of sample efficiency in reinforcement learning. José elaborates on deep generative models, their role in molecular property prediction, and strategies for enhancing the robustness of machine learning through invariant risk minimization. His research reveals exciting pathways in optimizing molecule discovery.