Reducing Operator Complexity in Algebraic Multigrid with Machine Learning Approaches

Efficient Training of Input Convex Neural Networks Using Variable Projection

Low-Rank Exploiting Optimization Methods for Inverse Problems and Machine Learning

Pre-Training Graph Neural Networks for Data-Efficient Brain Network Analysis

The Applications of Alternating Minimization Algorithms on Deep Learning Models

Linear Programming Approach for Q-Learning

Regularization of ill-posed inverse problems under mixed precision arithmetics

Nonnegative Matrix Factorization for Music - Tuning the NMF Algorithm with Regularization

Improving Multigrid Methods with Deep Neural Networks