November 20, 2023
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12:00 PM
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1:00 PM
Simulation-Based Inference: The Intersection of Mechanistic Models and Inverse Problems
Kyle Cranmer, PhD
Director of the UW-Madison Data Science Institute
Professor, Department of Physics
University of Wisconsin–Madison
Abstract:
Simulators are the modern manifestation of scientific theories. They implement mechanistic models of the underlying natural phenomena of interest as well as models for the instruments used to observe those phenomena. Complex, high-fidelity simulations have become critical research tools for predicting how systems will behave across many areas of science and engineering. Despite their predictive power, these simulators are poorly suited for statistical inference, which is a core aspect of data-intensive science. I will describe how machine learning is enabling simulation-based inference, an emerging set of techniques for solving these challenging inverse problems.
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