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
Time | Topic | Speaker |
10:00AM-11:00AM | Introduction to Probabilistic Programming for Bayesian Inference with Stan | Bob Carpenter |
11:00AM-11:20AM | Break | |
11:20AM-11:50AM | Advanced MCMC methods | Erik Thiede |
11:50AM-12:20PM | Hierarchical low rank compression and an application in many-body quantum physics | Hierarchical low rank compression and an application in many-body quantum physics |
12:20PM-1:00PM | Lunch | |
1:00PM-2:00PM | Equivariant neural nets for physical systems | Risi Kondor |
2:00PM-2:20PM | Break | |
2:20PM-2:50PM | Recurrent VAE for anomaly detection in supernova time series | Ashley Villar |
2:50PM-3:20PM | Differentiable programming for protein structure alignment | Jamie Morton |
3:20PM-3:40PM | Break | |
3:40PM-4:40PM | A Mathematical Introduction to Variational Quantum Monte Carlo with Deep Neural | James Stokes |
4:40PM-5:00PM | Break |
Time | Topic | Speaker |
10:00AM-11:00AM | Inverse problems, sparsity and neural network priors | Marylou Gabrie |
11:00AM-11:20AM | Break | |
11:20AM-11:50AM | Descartes versus bayes: Views of deep net theories | Stephane Mallat |
11:50AM-12:20PM | SARS-CoV-2 transmission in Marine recruits during quarantine and training | Rachel Sealfon |
12:20PM-1:00PM | Lunch | |
1:00PM-2:00PM | Interpretable machine learning with symbolic regression and graph networks | Miles Cranmer |
2:20PM-2:50PM | Discovering symbolic models in physical systems using deep learning | Shirley Ho |
2:50PM-3:20PM | An automated framework for efficiently designing deep convolutional neural | Zijun Zhang |
3:20PM-3:40PM | Break | |
3:40PM-4:40PM | Tensor networks and Itensor | Miles Stoudenmire |
4:40PM-5:00PM | Break |