Flatiron Internal Conference: Flatiron-wide Algorithms and Mathematics

Oct 19, 2020, 10:00 AM → Oct 20, 2020, 5:00 PM America/New_York

Flatiron-wide Algorithms and Mathematics (FWAM) is a 2 day internal conference with the goal of overviewing/introducing a range of numerical algorithms and tools that are essential to research done at Flatiron and beyond. We also aim to form research connections across (and within) the centers, and showcase some of the research which makes use of these methods. Topics have been chosen that are crucial to two or more centers.

An email with registration information was sent to all Flatiron members.

Recordings of the presentations can be found HERE.

Ashley Villar - fwam oct 2020 villar.pdf

Bob Carpenter - fwam2020-carpenter.pdf

Erik Thiede - Advanced_MCMC_corrected.pdf

Frank Zijun Zhang - 20201020-FWAM-zzhang.pptx

Jason Kaye - fwam20_jk.pdf

Marylou Gabrié - FWAM_MGabrie_InverseProblems.pdf

Miles Cranmer - sr_gnn_tutorial_50min_fwam_oct_2020_noninteractive.pdf

Miles Stoudenmire - TensorNetworks.pdf

Risi Kondor - Kondor FWAM.pdf

stephane mallat - MallatFlatIron2020v3.pdf

Monday, October 19

10:00 AM → 11:00 AM Tutorial: Introduction to Probabilistic Programming for Bayesian Inference with Stan

Convener: Bob Carpenter (CCM)

11:00 AM → 11:20 AM Break/Discussion

11:20 AM → 11:50 AM Case Study: Advanced MCMC methods

Convener: Erik Thiede (CCM)

11:50 AM → 12:20 PM Case Study: Hierarchical low rank compression and an application in many-body quantum physics

Convener: Jason Kaye (CCM)

12:20 PM → 1:00 PM Lunch/Discussion

1:00 PM → 2:00 PM Tutorial: Equivariant neural nets for physical systems

Convener: Risi Kondor (CCM)

2:00 PM → 2:20 PM Break/Discussion

2:20 PM → 2:50 PM Case Study: Recurrent VAE for anomaly detection in supernova time series

Convener: Ashley Villar (Simons Society of Fellows)

2:50 PM → 3:20 PM Case Study: Differentiable programming for protein structure alignment

Convener: Jamie Morton (CCB)

3:20 PM → 3:40 PM Break/Discussion

3:40 PM → 4:40 PM Tutorial: A Mathematical Introduction to Variational Quantum Monte Carlo with Deep Neural Networks

Convener: James Stokes (CCQ)

4:40 PM → 5:00 PM Break/Discussion

Tuesday, October 20

10:00 AM → 11:00 AM Tutorial: Inverse problems, sparsity and neural network priors

Convener: Marylou Gabrie (CCM)

11:00 AM → 11:20 AM Break/Discussion

11:20 AM → 11:50 AM Case Study: Descartes versus bayes: Views of deep net theories

Convener: Stephane Mallat (CCM)

11:50 AM → 12:20 PM Case Study: SARS-CoV-2 transmission in Marine recruits during quarantine and training

Convener: Rachel Sealfon (CCB)

12:20 PM → 1:00 PM Lunch/Discussion

1:00 PM → 2:00 PM Tutorial: Interpretable machine learning with symbolic regression and graph networks

Convener: Miles Cranmer (Princeton)

2:00 PM → 2:20 PM Break/Discussion

2:20 PM → 2:50 PM Case Study: Discovering symbolic models in physical systems using deep learning

Convener: Shirley Ho (CCA)

2:50 PM → 3:20 PM Case Study: An automated framework for efficiently designing deep convolutional neural networks in genomics

Convener: Zijun Zhang (CCB)

3:20 PM → 3:40 PM Break/Discussion

3:40 PM → 4:40 PM Tutorial: Tensor networks and ITensor

Convener: Miles Stoudenmire (CCQ)

4:40 PM → 5:00 PM Break/Discussion