Randomized algorithms for large scale linear algebra and data analytics

Graph Convolutional Neural Network via Scattering

Neural Network Quantization with a Probabilistic Version of Gradient Descent

A Spatio-Temporal Modeling Framework for Surveillance Data of Multiple Infectious Pathogens with Small Laboratory Validation Sets

Transport and Lagrangian transforms for signal analysis and machine learning

The Need for Physics-Informed Machine Learning in Hydrology

On Consistency of Graph-based Semi-supervised Learning

Towards Faster Large-scale Nonconvex Optimization via Variance Reduction

Structure Enhancing Algorithms and Losses in Non-Convex LearningProblems

New Algorithms and Improved Guarantees for One-Bit Compressed Sensing on Manifolds

Considering Cognitive Bias during Interactive Visual Analytics

Sketching Distances in Graphs

New Applications of Nearest-Neighbor Chains

Enhancing Visual Data Analysis through Demonstrational User Interaction

Eidos, INDRA & Delphi: From Free Text to Executable Causal Models

Pairwise Metamodeling of Multivariate Output Simulation Models