Michael U. Gutmann

I am a Senior Lecturer (Assoc Prof) in Machine Learning at the School of Informatics of the University of Edinburgh, affiliated with the Institute for Machine Learning.

My research is in machine learning for science, with a focus on developing methods for (Bayesian) inference and design.

A short biography is available here.

Recent papers

• NeurIPS: Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences [link]

• arXiv: Amortized Thompson Sampling and Efficient Information-Directed Sampling for Simulator-Based Design [link]

• arXiv: Sequential Design of Genetic Circuits Under Uncertainty With Reinforcement Learning [link]

• Cell Systems: Risk-averse optimization of genetic circuits under uncertainty [link]