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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
January 16, 2024Francois LanusseMerging Deep Learning with Physical Models for the Analysis of Cosmological Galaxy Surveys
January 23, 2024Francesca MignaccoStatistical physics insights into the dynamics of learning algorithms
February 6, 2024Alex WiltschkoMapping scent
February 20, 2024Tim RudnerData-Driven Priors for Trustworthy Machine Learning
March 5, 2024Sam RodriguesAutomating Research at FutureHouse
April 2, 2024Soledad VillarExact and approximate symmetries in machine learning
April 16, 2024David FouheyAdventures in Using Computer Vision for Solar Physics and Space Weather
April 30, 2024Mengye RenLifelong and Human-like Learning in Foundation Models
May 28, 2024Leila WehbeTBD
June 11, 2024Mark CheungTBD
June 25, 2024Sonya HansonTBD
September 17, 2024Grace LindsayTBD
October 1, 2024Andrea LiuTBD

Past Series

2023 Machine Learning at the Flatiron Institute Seminar 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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