Scientific Machine Learning (SciML) is concerned with the development of...
Bilevel Optimization Programming is used to model complex and conflictin...
Machine learning-based modeling of physical systems has experienced incr...
With Human-Centric Research (HCR) we can steer research activities so th...
Graph sparsification aims to reduce the number of edges of a graph while...
Deep neural networks suffer from poor generalization to unseen environme...
Measuring the dependence of data plays a central role in statistics and
...
In this paper, we propose a continual learning (CL) technique that is
be...
We present a novel methodology to jointly perform multi-task learning an...
Interpretable Multi-Task Learning can be expressed as learning a sparse ...
We propose a simple yet powerful test statistic to quantify the discrepa...
Many real-world large-scale regression problems can be formulated as
Mul...