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2020 Flatiron Wide Algorithms and Mathematics

Conference

Computational Mathematics

When

  • All Day

  • All Day

Where

Virtual

160 Fifth Avenue

New York, NY 10010

FWAM (“Flatiron-wide Autumn Meeting”, previously “Flatiron-wide Algorithms and Mathematics”) is a two-day internal conference with the goal of introducing and reviewing scientific and computational tools of broad and significant usefulness to Flatiron researchers across all centers of the institute.

Agenda

October 19, 2020

Erik Thiede: Advanced Methods in Markov Chain Monte Carlo

October 19, 2020

Jason Kaye: Hierarchical Low Rank Compression, With an Application in Quantum Many-Body Physics

October 19, 2020

Risi Kondor: Equivariant Neural Networks for Learning Physical Systems

October 19, 2020

Ashley Villar: Recurrent VAE for Anomaly Detection in Supernova Time Series

October 19, 2020

Bob Carpenter: Probabilistic Programming and Bayesian Interference with Stan

October 20, 2020

Marylou Gabrié: Inverse Problems, Sparsity and Neural Network Priors

October 20, 2020

Stephane Mallat: A Harmonic Analysis View of Deep Network Theory

October 20, 2020

Miles Cranmer: Interpretable Machine Learning, Using Symbolic Regression and Graph Neural Networks

October 20, 2020

Zijun Zhang: AutoML for Functional Genomics

October 20, 2020

Miles Stoudenmire: Tensor Networks and iTensor

October 20, 2020

Shirley Ho: Learning Symbolic Equations with Deep Learning
Flatiron Institute Illustration

Event Series

Flatiron Wide Autumn Meeting

A two-day internal conference with the goal of introducing and reviewing scientific and computational tools of broad and significant usefulness to Flatiron Institute researchers across all centers.

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Speakers

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