No equations, no variables, no parameters, no space and no time - some new and some old results in data-driven modeling of complex dynamical systems
Yannis Kevrekidis
Johns Hopkins University
January 29, 2019
Nonlinear reduced-order modeling - Using machine learning to enable extreme-scale simulation for many-query problems
Kevin Carlberg
Sandia National Laboratories
January 29, 2019
Data-driven model discovery and coordinate embeddings for physical systems
J. Nathan Kutz
University of Washington
January 29, 2019
Deep Neural Networks and Partial Differential Equations - Approximation Theory and Structural Properties
Philipp Petersen
University of Oxford
January 29, 2019
Collapse of deep and narrow neural nets
Lu Lu
Brown University
Yeonjong Shin
Brown University
January 28, 2019
Hidden Physics Models - Machine Learning of Non-Linear Partial Differential Equations
Maziar Raissi
NVIDIA
January 28, 2019
A new perspective on machine learning
Hrushikesh Mhaskar
Claremont Graduate University
January 28, 2019
Deep Neural Network, Finite Element and Multigrid
Jinchao Xu
Pennsylvania State University
January 28, 2019
Which ReLU Net Architectures Give Rise to Exploding and Vanishing Gradients
Boris Hanin
Texas A&M University
January 28, 2019