A Bayesian neural network predicts the dissolution of compact planetary systems
Virtualhttps://youtu.be/VhseP2V3NXg Speaker: Miles Cranmer - Princeton University Title: A Bayesian neural network predicts the dissolution of compact planetary systems Abstract: Despite over three hundred years of effort, no solutions exist for predicting when a general planetary configuration will become unstable. I will discuss our deep learning architecture (arxiv:2101.04117) which pushes forward this problem for compact systems. […]
CMSA Math-Science Literature Lecture: Deep Networks from First Principles
VirtualYi MaPhoto Copyright Noah Berger / 2019 Yi Ma (University of California, Berkeley) Title: Deep Networks from First Principles Abstract: In this talk, we offer an entirely “white box’’ interpretation of deep (convolution) networks from the perspective of data compression (and group invariance). In particular, we show how modern deep layered architectures, linear (convolution) operators and […]
CMSA Math-Science Literature Lecture: The Atiyah-Singer Index Theorem
VirtualDan Freed (The University of Texas at Austin) Title: The Atiyah-Singer Index Theorem Abstract: The story of the index theorem ties together the Gang of Four—Atiyah, Bott, Hirzebruch, and Singer—and lies at the intersection of analysis, geometry, and topology. In the first part of the talk I will recount high points in the early developments. Then I […]