See the main website for more! We look forward to MLonMB on November 10, 2021 from 9am-3:30pm at the UCSC Hay Barn (coffee and fruit will be available from 8am-9am). Our last requests of you prior to the meeting are…
When: 9am PT, noon ET, 6pm CET How: http://MLclub.net Who: Yuan-Sen Ting (IAS) Kim Venn (Victoria) Keith Hawkins (Texas) David W. Hogg (NYU) Title: “Will Machine Learning Solve the Analysis of Stellar Spectroscopy?” Abstract: An online…
When: 9am PT, noon ET, 6pm CET How: http://MLclub.net Who: Helena Dominguez-Sanchez (ICE) Sandra M. Faber (UCSC) Josh Peek (STScI) Simon D.M. White (MPA) Title: “Galaxy Morphology in the machine learning era: revolution or incremental science?”…
When: 9am PT, noon ET, 5pm CET How: http://MLclub.net Who: Gary Bernstein (UPenn) Olivier Ilbert (LAM, Marsielle) Alex Malz (Ruhr U., Bochum) Emmanuel Bertin (LAP, Paris) Title: “Will Machine Learning solve photometric redshifts?” Abstract: An online debate on the challenges…
When: 9am PT, noon ET, 6pm CET How: http://MLclub.net Who: Julia Kempe (NYU Center for data science) David Spergel (Flatiron institute) Alex Szalay (John Hopkins Univ.) J. Xavier Prochaska (UC Santa Cruz, AAII) Title: “How should ML penetrate the natural…
Save the dates: March 23, 9am – 12pm. March 26, 9am – 12pm. Check back with us. Details forthcoming!
When: 9am PT (with the ML Club) How: Webinar link Who: Francois Lanusse (CNRS; CEA Saclay) Marc Huertas-Company (U. Paris; IAC) Brice Menard (Johns Hopkins) J. Xavier Prochaska (UC Santa Cruz, AAII) Title: “What is Deep Learning Teaching Astronomy?” Abstract:…
When: 9am PT (with the ML Club) How: Zoom link = https://ucsc.zoom.us/j/272379932 Who: Sebastian Wetzel (Perimeter Institute for Theoretical Physics, Canada) Title: “Siamese Neural Networks Learn Symmetry Invariants and Conserved Quantities” Abstract: In this talk, we discuss Siamese Neural Networks…
When: 9am PT (with the ML Club) How: Zoom link = https://ucsc.zoom.us/j/272379932 Who: Jared Kaplan (Johns Hopkins / OpenAI) Title: “GPT-3, the most powerful language model, and neural scaling laws” The work is based on this paper: https://arxiv.org/abs/2005.14165
When: 9am PT How: Here is the Zoom link: https://ucsc.zoom.us/j/272379932 Who: François Charton (Facebook) and Amaury Hayat (Pasitech, Rutgers) Title: “Learning maths from example with deep language models” Abstract: In this presentation we show how to use deep language models to…