6-8 p.m. — Welcome Reception, Light Reception Fare will be served

Monday, January 22, 2018

8-9 a.m. — Breakfast

9-9:30 a.m. — Introduction, Alan Bishop, Principle Associate Director of Science, Technology, and Engineering at Los Alamos National Laboratory

9:30-10:10 a.m.—Invited Talk, Carlo Baldassi, "Synaptic [classical and quantum] Fluctuations as a Recipe for Robust and Efficient Neural Network Training" Presentation

10:10-10:50 a.m.—Invited Talk, Greg Ver Steeg, "Blessings of Dimensionality for Gaussian Latent Factor Models" Presentation

10:50-11:20 a.m. — Break

11:20-noon—Invited Talk, Alex Gorodetsky, "Multifidelity Model Management using Latent Variable Bayesian Networks"

Noon-12:20 p.m.— Contributed Talk, Insu Han, "Approximating and Optimizing Spectral Matrix Functions for Large-scale Matrices using Stochastic Chebyshev Expansion" Presentation

12:20-2 p.m. — Lunch

2-2:40 p.m.— Invited Talk, David Saad, "Error and Entropy in the Function Space of Multi-layer Networks" Presentation

2:40-3:20 p.m.— Invited Talk, Surya Ganguli, "On the Beneficial Role of Dynamic Criticality and Chaos in Deep Learning"

3:20-3:50 p.m. — Break

3:50-4:30 p.m.— Invited Talk, Paul Johnson, "Machine Learning in Faulting Physics"

4:30-5:10 p.m.— Invited Talk, Eric Mjolsness, "Multiscaling with Learning in Stochastic Physical Models"

Tuesday, January 23, 2018

8-9 a.m. — Breakfast

9-9:40 a.m. — Invited Talk, Miles Stoudenmire, "Learning Relevant Features of Data with Multiscale Tensor Networks"Presentation

9:40-10:20 a.m. — Invited Talk, Dong-Lin Deng, "Machine Learning Quantum States, Many-body Entanglement and Bell Non-locality"

10:20-10:50 a.m. — Break

10:50-11:30 a.m. —Invited Talk, Marc Vuffray, "Unraveling Quantum Annealers with Machine Learning" Presentation

11:30-11:50 a.m.—Contributed Talk, Marin Bukov, "Reinforcement Learning in Different Phases of Quantum Control" Presentation

11:50-12:10 p.m.— Contributed Talk, Sungsoo Ahn, "Renormalization Group of Graphical Models"

12:10-2 p.m. — Lunch

2-2:40 p.m.— Invited Talk, Yan Liu, "Neural Interaction Detector - Detecting High-order Interactions via Deep Neural Networks" Presentation

11:30-11:50 a.m.—Contributed Talk, Yeesian Ng, "Statistical Learning for DC Optimal Power Flow"

11:50-12:20 p.m.— Contributed Talk, Chiyu Jiang, " Deep Learning Based Geometry Encoding for Physics Aware Surrogate Modeling and Transfer Learning" Presentation

2:40-3:20 p.m.— Invited Talk, Gowri Sirinivasan, "Discovering Reduced Graph-based Models of Fracture Networks using Machine Learning"

3:20-3:50 p.m. — Break

3:50-4:50 p.m.—Discussion Session- "What does Physics Informed Machine Learning mean to you?"

5:00-6:30 p.m.— Poster Session

6:30-8:30 p.m.— Banquet Dinner

Thursday, January 25, 2018

8-9 a.m. — Breakfast

9-9:40 a.m. — Invited Talk, Olexander Isayev, "Towards Universal ML Potential for Organic Molecules"

9:40-10:00 a.m.—Contributed Talk, Justin Smith, "Chemical Space Sampling with Active Learning"

10:00-10:20 a.m.— Contributed Talk, Konstantin Gubaev, "Machine Learning Interatomic Potentials for Multicomponent Systems" Presentation

10:20-10:50 a.m. — Break

10:50-11:30 a.m. —Invited Talk, Luca Biferale, "Flow Navigation by Smart Particles via Reinforcement Learning" Presentation

11:30-11:50 a.m.— Contributed Talk, Arvind Mohan, "Reduced Order Modeling of Turbulent Flows using Long Short Term Memory Neural Networks" Presentation

11:50-12:10 p.m.— Contributed Talk, Oliver Hennign, "Lat-Net: Compressing Lattice Boltzmann Flow Simulations using Deep Neural Networks"

12:10-2 p.m. — Lunch

2-2:40 p.m.— Invited Talk, Ryan King, "Deep Learning for Generating Fully-Developed Turbulent Flows"