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SUMMARY:CS Seminar Series: A First-Principles Approach to Deep Learning and Applications to Quantum Materials
DESCRIPTION:Refreshments are available starting at 10:30 a.m. The seminar will begin at 10:45 a.m. \nAbstract\nRecent years have seen unprecedented advancements in the development of machine learning and artificial intelligence. For the applied sciences\, these tools offer new paradigms for combining insights developed from theory\, computation\, and experiments towards design and discovery\, and for bridging the microscopic world with the macroscopic. Beyond treating them as black boxes\, however\, uncovering and distilling the fundamental principles behind how systems built with neural networks work is a grand challenge\, and one that can be aided by ideas\, tools\, and methodologies from physics. Yasaman Bahri will describe one pillar of her research that takes a first-principles approach to deep learning through the lens of statistical physics\, exactly solvable models and mean-field theories\, and nonlinear dynamics. She will discuss new connections she discovered between large-width deep neural networks\, Gaussian processes\, and kernels; the emergence of linear models during training and phase transitions away from them; experimentally-consistent insights into scaling laws; and an outlook on the next frontiers in this research program. She will then discuss the early stages of a second research program proceeding in the reverse direction\, in which a deeper understanding of ML and AI can be used to advance the quantum sciences and quantum materials. As an early example\, Bahri considers physics as a domain to examine recall and reasoning in large language models. She will describe work investigating the ability of such models to perform analytic Hartree-Fock mean-field calculations in quantum many-body physics. \nSpeaker Biography\nYasaman Bahri is a research scientist at Google DeepMind. Her research lies at the confluence of machine learning and the physical sciences. She completed her PhD in physics at the University of California\, Berkeley as an NSF Graduate Fellow\, specializing in the theory of quantum condensed matter. Her doctoral work investigated quantum matter through the themes of topology\, symmetry\, and localization. She has been an invited lecturer at the Les Houches School of Physics\, is a past Rising Star in Electrical Engineering and Computer Science\, and was a co-organizer of a recent program on deep learning at the Kavli Institute for Theoretical Physics. \nZoom link >>
URL:https://www.cs.jhu.edu/event/cs-seminar-series-a-first-principles-approach-to-deep-learning-and-applications-to-quantum-materials/
LOCATION:Hackerman B-17
CATEGORIES:Seminars and Lectures
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