2022 Flatiron Wide Algorithms and Mathematics

Videos

October 27, 2022

• Manas Rachh: Efficient Representation of Low-Dimensional Functions: Interpolation and Integration in Low Dimensions

• Scott Weady: Efficient Representation of Low-Dimensional Functions: Maximum Entropy Closure for Kinetic Theories of Complex Fluids

• Olivier Parcollet: Efficient Representation of High-Dimensional Functions: Tensor Network Compression for High Dimensional Integration and its Application to Feynman Diagrams

• Fruzsina Agocs: Ordinary Differential Equations: Numerical Solution of ODEs: a Practical Guide

• Chris White: Ordinary Differential Equations: Physical Considerations for When Time Integration of Gas Dynamics Fails

• Charles Margossian: Ordinary Differential Equations: Solving ODEs in a Bayesian Model

October 28, 2022

• Michael Eickenberg: Practical Tools for Machine Learning and Data Science: Into to ML Linear Regression Scikit-Learn from Scratch

• Robert Gower: Practical Tools for Machine Learning and Data Science: Stochastic Gradient Descent, Tricks, Learning Rates, and Momentum

• Lily Zhao: Practical Tools for Machine Learning and Data Science: Improving Exoplanet Detection with Discriminative Linear Regression

• Dhairya Malhotra: High Performance Computing: What Every Programmer Should Know About High Performance Computing

• Robert Blackwell & Geraud Krawezik: High Performance Computing: GPUs: The Good, The Bad and the Ugly

• Lehman Garrison: High Performance Computing: How Not to Write a High-Performance N-body Code