IFML Seminar
IFML Seminar: 10/03/25 - Successor Measures and Self-supervised Reinforcement Learning
Abstract: We introduce a method for learning behavioral foundation models using the successor measure. We show that any visitation distribution can be represented using an affine combination of policy-independent basis functions. By learning these...
Upcoming Events
- October312:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: We introduce a method for learning behavioral foundation models using the successor measure. We show that any visitation distribution...
- October1012:15 - 1:15pm
IFML Seminar
Event DetailsABSTRACT: What would it mean for AI to understand skilled human activity? In augmented reality (AR), a person wearing smart...
- October2412:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Learning from sequential, temporally-correlated data is a core facet of modern machine learning and statistical modeling. Yet our fundamental...
Past Events
- December1312:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Deep neural networks (DNNs) have become popular tools to solve ill-posed image recovery problems, such as those associated with...
- December101:30 - 4 pmEvent Details
One of the most striking findings in modern research on large language models (LLMs) is that, given a model and...
- December612:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Computer vision has made remarkable advances through data-driven learning of image-text associations. Large-scale vision and language models like…
- December45:30 - 8 pm
Public Lecture
Event DetailsPublic event hosted by IBM, the Austin AI Alliance, and the Global AI Alliance (co-founded by IBM). Our Deep Proteins...
- November1512:15 - 1:15pm
IFML Seminar
Event DetailsSpeaker Bio: Zak Mhammedi is a Research Scientist at Google Research , focusing on reinforcement learning and optimization. He completed...
- November13throughNovember15Event Details
Join us for UT Austin’s Year of AI celebration as we showcase the best ideas, innovations and inspiration in the...
