Workshop IV: Synergies between Machine Learning and Physical Models - IPAM

Workshop IV: Synergies between Machine Learning and Physical Models

Part of the Long Program Understanding Many-Particle Systems with Machine Learning
December 5 - 8, 2016

Schedule

All times in this Schedule are Pacific Time (PT)

Monday, December 5, 2016

Morning Session

08:00-08:55
Check-In/Light Breakfast (Hosted by IPAM)
08:55-09:00
Welcome and Opening Remarks
09:00-09:50
Efthimios (Tim) Kaxiras (Harvard University)
Machine Learning for the Materials World
10:00-10:15
Break
10:15-11:05
Yuval Peres (Microsoft Research)
Using random walks to analyze Prediction with Expert Advice
11:15-11:30
Break
11:30-12:20
Ralf Banisch (Freie Universität Berlin)
Learning dynamics with dynamical distances: From diffusion maps to commute maps and coherence

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Soumik Pal (University of Washington)
Markov chains on partitions and their diffusion analogs
15:30-16:00
Break
16:00-16:50
Marina Meila (University of Waterloo)
Geometric manifold learning methods and collective variables
17:00-18:30
Poster Session & Reception (Hosted by IPAM)

Tuesday, December 6, 2016

Morning Session

08:15-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Alán Aspuru-Guzik (University of Toronto)
Machine learning for organic materials design
10:00-10:15
Break
10:15-11:05
Geoffrey Hutchison (University of Pittsburgh)
Learning from Conjugated Polymers: Statistical Data Mining from 50 Million and Counting
11:15-11:30
Break
11:30-12:20
Kyle Michel (Citrine Informatics)
The study of materials systems through machine learning and physical models

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Eric Stahlberg (National Cancer Institute)
Accelerating Cancer Research Using Advanced Computing Solutions
15:30-16:00
Break
16:00-16:50
Aram Harrow (Massachusetts Institute of Technology)
Quantum Monte Carlo vs Tunneling in Adiabatic Optimization

Wednesday, December 7, 2016

Morning Session

08:15-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Matthew Spellings (MLPRC2)
Navigating colloidal design space with machine learning
10:00-10:15
Break
10:15-11:05
Ioana Dumitriu (University of Washington)
Two Clustering Problems for the Stochastic Block Model
11:15-11:30
Break
11:30-12:20
David Beratan (Duke University)
Molecular discovery in silico and in cranio

Afternoon Session

12:30-14:00
Lunch (on your own)
14:00-14:50
Sadasivan Shankar (Harvard University)
Machine Learning for Materials Design: Combination of Theoretical methods, Heuristics, and Hybrid Techniques
15:00-15:15
Break
15:15-16:05
Rebecca Willett (University of Chicago)
Sparsity and Scarcity in Discrete Event Data Analysis
16:15-16:30
Break
16:30-17:20
Alvaro Vazquez-Mayagoitia (Argonne National Laboratory)
Large Data production and workflows for materials discovery using parallel computing

Thursday, December 8, 2016

Morning Session

08:15-09:00
Check-In/Breakfast (Hosted by IPAM)
09:00-09:50
Johannes Hachmann (SUNY Buffalo)
A Software Ecosystem for the Data-Driven Design of Chemical Systems and the Exploration of Chemical Space
10:00-10:15
Break
10:15-11:05
John Parkhill (University of Notre Dame)
TensorMol 0.0 a Package for Statistical Models of Molecular Structure
11:15-11:30
Break
11:30-12:20
Thomas Bliggard (Stanford University)
Utilizing machine learning to accelerate computational catalyst search

Afternoon Session

12:30-12:30
Conclusion
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