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ML@FI Seminar Series

ML@FI is a seminar series focused on machine learning and its applications to science. It is aimed at Flatiron Institute research scientists and our collaborators. Seminars usually take place on every other Tuesday at 3:00 p.m. Each seminar is followed by a reception to encourage intercenter interactions.

For more information, to join the seminar mailing list or to propose speakers for future seminars, please contact the organizers: Shirley Ho, Siavash Golkar, Anna Dawid or Michael Eickenberg.

2023 Schedule

DateSpeakerTitle
February 7, 2023Chirag ModiReconstructing the initial conditions of the Universe
March 7, 2023Jean PoncePhysical models and machine learning for Photography and Astronomy
March 14, 2023Ching-Yao LaiPhysics-informed neural networks for fluid and ice dynamics
April 11, 2023Laure ZannaMachine learning for climate modeling
April 18, 2023Tammy KoldaGeneralized tensor decomposition: Utility for data analysis and mathematical challenges
April 25, 2023Dmitri KochkovNumerical methods + ML for simulation of turbulent systems
May 2, 2023David HoggIs good machine learning bad for science?
September 19, 2023Eero SimoncelliPhotographic Image Priors in the Era of Machine Learning
October 3, 2023Alberto BiettiTransformers and Associative Memories
October 17, 2023David PfauNatural Quantum Monte Carlo Computation of Excited States
October 31, 2023Sebastian J WetzelFinding Symmetry Invariants and Conserved Quantities with Artificial Neural Networks
November 14, 2023Eliška GreplováTBA

Past Series

2022 Machine Learning at the Flatiron Institute Seminar Series

2021 Machine Learning at the Flatiron Institute Seminar Series

2020 Machine Learning at the Flatiron Institute Seminar Series

2019 Machine Learning at the Flatiron Institute Seminar Series

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