H. F. DeLuca Forum

SILO: Decision-Aware Models for Adaptive Experimentation and Bayesian Optimization

Abstract: Machine learning and AI models hold great promise for accelerating scientific discovery by intelligently planning experiments and learning from their results. While existing models can be applied in this setting, I will argue in this talk for decision-aware models designed explicitly for adaptive experimentation tasks rather than traditional predictive …

Model-Predictive Policy Learning with Uncertainty Regularisation for Driving in Dense Traffic

Learning a policy using only observational data is challenging because the distribution of states it induces at execution time may differ from the distribution observed during training. In this work, we propose to train a policy while explicitly penalising the mismatch between these two distributions over a fixed time horizon. …