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TILOS Seminar: Towards Foundation Models for Graph Reasoning and AI 4 Science Michael Galkin, Research Scientist at AI Lab HDSI 123 and Zoom: https://ucsd.zoom.us/j/99334315002 Abstract: Foundation models in graph learning are […]
Recent advances in computing hardware (FPGAs, distributed parallel computing) and numerical methods (machine learning algorithms, automatic differentiation) create new possibilities for Fusion Power Plant optimization and control. In this talk, I will discuss some of the recent accomplishments of the Plasma Control Group at Princeton that take advantage of these new capabilities.
How did scientists make sense of data before statistics and computing? This talk will explore this question by focusing on the discovery of vitamins, which occurred in the early 20th century just before the advent of modern statistical methodology. I will describe the varied practices in experimentation and reporting and highlight the sorts of insights required to uncover what "works." Through this discussion, I will draw connections to contemporary data science tools to illustrate their pros and cons in facilitating discovery.