Workshop I: Tensor Methods and their Applications in the Physical and Data Sciences - IPAM

Workshop I: Tensor Methods and their Applications in the Physical and Data Sciences

Part of the Long Program Tensor Methods and Emerging Applications to the Physical and Data Sciences
March 29 - April 1, 2021

Schedule

All times in this Schedule are Pacific Time (PT)

Monday, March 29, 2021

Morning Session

07:55-07:55
SESSION CHAIR: Reinhold Schneider (Technische Universität Berlin)
07:55-08:00
Welcome & Opening Remarks: Dean Miguel García-Garibay (Dean of Physical Sciences, UCLA) and Dima Shlyakhtenko (Director, IPAM)
08:00-08:30
Markus Bachmayr (Johannes Gutenberg-Universität Mainz)
Particle Number Conservation and Block-Sparse Matrix Product States
08:40-08:55
Break
08:55-09:25
Laura Grigori (Sorbonne Université)
Tensor compression through hierarchical tensor partitioning
09:35-09:50
Break
09:50-10:20
Lars Grasedyck (RWTH Aachen University)
Multigrid in Hierarchical Low Rank Tensor Formats
10:30-10:45
Break
10:45-11:15
André Uschmajew (Max-Planck-Institut für Mathematik in den Naturwissenschaften)
Dynamical low-rank approximation for parabolic problems
11:25-11:40
Lightning Poster Round
11:40-12:15
Poster Session

Tuesday, March 30, 2021

Morning Session

08:00-08:00
SESSION CHAIR: Miles Stoudenmire (Flatiron Institute)
08:00-08:30
Anthony Nouy (Université de Nantes)
Approximation and learning with tree tensor networks
08:40-08:55
Break
08:55-09:25
Vladimir Kazeev (Universität Wien)
Data-driven discretization of PDEs via tensor refinement
09:35-09:50
Break
09:50-10:20
Reinhold Schneider (Technische Universität Berlin)
Solving Backward Stochastic Differential Equation and Hamilton Jacobi Bellmann (HJB) equations with Tree Based Tensor Networks (HT/TT)
10:30-10:45
Break
10:45-11:15
Ming Yuan (Columbia University)
Low rank tensor completion
11:25-11:55
Lei Wang (Chinese Academy of Sciences)
Tropical Tensor Networks

Wednesday, March 31, 2021

Morning Session

08:00-08:00
SESSION CHAIR: André Uschmajew (Max-Planck-Institut für Mathematik in den Naturwissenschaften)
08:00-08:30
Nadav Cohen (Tel Aviv University)
Implicit Regularization in Deep Learning: Lessons Learned from Matrix and Tensor Factorization
08:40-08:55
Break
08:55-09:25
Virginie Ehrlacher (École des Ponts ParisTech)
Tensorized Adaptive Biasing Force method for molecular dynamics simulations (joint work with Tony Lelièvre and Pierre Monmarché)
09:35-09:50
Break
09:50-10:20
Peter Benner (Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg)
Parallel Algorithms for Tensor Train Arithmetic
10:30-10:45
Break
10:45-11:15
Miles Stoudenmire (Flatiron Institute)
Tensor Networks for Machine Learning and Applications

Thursday, April 1, 2021

Morning Session

08:00-08:00
SESSION CHAIR: Micheline Soley (Yale University)
08:00-08:30
Ulrich Schollwöck (University of Munich)
Matrix product states for real materials
08:40-08:55
Break
08:55-09:25
Nithin Govindarajan (KU Leuven )
Joint talk with Lieven De Lathauwer (Katholieke Universiteit Leuven): Spline-based separable expansions for approximation, regression and classification
09:35-09:50
Break
09:50-10:20
Aram Harrow (Massachusetts Institute of Technology)
Phase transitions in the complexity of simulating random shallow quantum circuits
10:30-10:45
Break
10:45-11:15
Nick Mayhall (Virginia Polytechnic Institute and State University)
Selected Configuration Interaction in a Basis of Cluster State Tensor Products
11:25-11:40
Break
11:40-12:10
Johnnie Gray (California Institute of Technology)
Hyper-optimized tensor network contraction - simplifications, applications and approximations
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