Yuli Slavutsky (Columbia): “Adaptive Bayesian Models for Reliable Uncertainty”
Abstract:
Modern AI systems offer impressive predictive abilities, but often struggle to provide reliable uncertainty estimates. This challenge arises when the distribution of new inputs differs from that seen during training, for example when broadly pretrained models are adapted to specialized downstream tasks. Classical Bayesian models provide a principled framework for uncertainty quantification, but do not directly address this setting: a new covariate changes where the posterior predictive distribution is evaluated, but not the posterior over the predictive mechanism itself. At the same time, methods designed to account for distribution shifts typically respond to distributional change itself, even when predictive ability is unaffected.
In this talk, I will present covariate-dependent Bayesian models, in which the prior depends on both the training covariates and the queried covariate, but not on the outcomes. Constructing the prior from the likelihoods of the predictive models ties this adaptation directly to predictive ability, rather than to distributional change alone. We will discuss two instantiations: covariate-dependent priors on prediction-layer parameters, which yield uncertainty estimates that adapt to shifts affecting predictive performance, and random selection models over fixed predictors whose posterior probabilities yield input-adaptive averaging weights.
Biography:
Yuli Slavutsky is a Founder’s Postdoctoral Research Scientist in the Department of Statistics at Columbia University. Her research develops Bayesian and variational methods for reliable prediction, with a focus on uncertainty quantification and robust representation learning. She received her PhD in Statistics and Data Science from the Hebrew University of Jerusalem, advised by Yuval Benjamini, and her master’s degree in Statistics from the same institution, advised by Or Zuk. Prior to her PhD, she worked in industry as a data scientist and research team leader.
Zoom: https://upenn.zoom.us/j/97645937545
