Machine Learning X Summer School Lecture Series

Jun 6, 2022, 9:00 AM → Jun 17, 2022, 5:00 PM America/New_York

14th Floor (MfA)

YouTube Playlist

Monday, June 6

9:00 AM → 10:30 AM "Introduction to ML"; "Syllabus Day" | Speaker: Miles Cranmer

11:00 AM → 12:30 PM "Optimization for ML: First-order methods" | Speaker: Rob Gower

Day 1 Lectures

Gower_Flatiron_summer_school.pdf

Tuesday, June 7

9:00 AM → 10:30 AM "Optimization for ML: Stochastic Gradient Descent" | Speaker: Rob Gower

Gower_Flatiron_summer_school.pdf

11:00 AM → 12:30 PM "Introduction to Deep Learning in Python: Architectures, optimizers, tips for tuning DL loop" | Speaker: Wenda Zhou

1:30 PM → 3:00 PM "Linear Regression and Linear Models" | Speaker: David Hogg

3:30 PM → 5:00 PM "ML for quantum physics: Ground state properties" | Speaker: Guiseppe Carleo

Day 2 Lectures

Wednesday, June 8

9:00 AM → 10:30 AM "Learning dynamics from data Latent variables Dynamic mode decomposition" | Speaker: Anirvan Sengupta

11:30 AM → 1:00 PM "Dimension Reduction: visualization, validation, and downstream analyses" | Speaker: Barbara Engelhardt

3:30 PM → 4:30 PM "Self-Supervised Learning, Energy-based Methods, and World Models" | Speaker: Yann LeCun

Day 3 Lectures

Thursday, June 9

11:00 AM → 12:30 PM "Learning to Cooperate and Compete in Diplomacy" | Speaker: Noam Brown

2022-06 Flatiron Diplomacy.pptx

1:30 PM → 3:00 PM "Interpretable Machine Learning, and Symbolic Regression" | Speaker: Miles Cranmer

3:30 PM → 5:00 PM "Mathematical Models of Deep Neural Networks" | Speaker: Stephane Mallat

Day 4 Lectures

Friday, June 10

9:00 AM → 10:30 AM "Automatic differentiation" | Speaker: Mario Lezcano

11:00 AM → 12:30 PM "Representation geometry in biological and artificial networks" | Speaker: SueYeon Chung

1:30 PM → 3:00 PM "ML for Quantum Physics: State Reconstruction, Dynamics, Applications" | Speaker: Giuseppe Carleo

3:30 PM → 5:00 PM "Variational Monte Carlo with neural network quantum states" | Speaker: Javier Robledo Moreno

Day 5 Lectures

Monday, June 13

11:00 AM → 12:30 PM "Intro to neural networks on spatial data" | Speaker: Wenda Zhou

1:30 PM → 3:00 PM "Fermionic Wave Functions" | Speaker: Javier Robledo Moreno

3:30 PM → 5:00 PM "Biological Machine Learning" | Speaker: Mitya Chklovskii

Day 6 Lectures

Tuesday, June 14

11:00 AM → 12:30 PM "Intro to Gaussian Processes" | Speaker: Dan Foreman-Mackey

ml-summer-school.pdf

1:30 PM → 3:00 PM "Intro to MCMC" | Speaker: Kaze Wong

3:30 PM → 5:00 PM "TBD" | Speaker: Kyunghyun Cho

Day 7 Lectures

Wednesday, June 15

9:00 AM → 11:00 AM "Matrix Factorization" | Speaker: Alex Williams

11:00 AM → 12:30 PM "Intro to Statistical Learning Theory" | Speaker: Alex Williams

3:30 PM → 5:00 PM "Introduction to ML in Astrophysics" | Speaker: Shirley Ho

Thursday, June 16

1:30 PM → 3:00 PM "Enhancing sampling with learning: MCMC, generative models and overlaps " | Speaker: Marylou Gabrié

Marylou Gabrie_enhancing_sampling.pdf

3:30 PM → 5:00 PM "AMBER Deep learning in genomics" | Speaker: Frank Zijun Zhang

20220611-FlatironMLsummer.pdf

Friday, June 17

9:00 AM → 10:30 AM "ML for quantum physics" | Speaker: Giuseppe Carleo

11:00 AM → 12:30 PM "Bayesian model evaluation, selection, and aggregation" | Speaker: Yuling Yao