Past talk · AI/ML Seminar Series
Use Cases for Bayesian Deep Learning in the Age of ChatGPT
Research group leader in Machine Learning, Helmholtz AI
- Date & time
- Thursday, July 20, 2023 · 11:00 AM
- Location
- Donald Bren Hall 3011
Abstract
Many researchers have pondered the same existential questions since the release of ChatGPT: Is scale really all you need? Will the future of machine learning rely exclusively on foundation models? In this talk, I will try to make the case that the answer should be a convinced no and that now, maybe more than ever, should be the time to focus on fundamental questions in machine learning again. I will provide evidence by presenting three modern use cases of Bayesian deep learning in the areas of self-supervised learning, interpretable additive modeling, and sequential decision making. Together, these will show that the research field of Bayesian deep learning is very much alive and thriving.
About the speaker
Vincent Fortuin is a tenure-track research group leader at Helmholtz AI in Munich, leading the group for Efficient Learning and Probabilistic Inference for Science (ELPIS), and a Branco Weiss Fellow. His research focuses on reliable and data-efficient AI approaches leveraging Bayesian deep learning. Before that, he did his PhD in Machine Learning at ETH Zürich and was a Research Fellow at the University of Cambridge.