This document provides an overview of our research focus, ongoing projects, future directions, and resources, particularly concerning our work in Differentiable Programming (DP). Differentiable ...

In recent years there has been an explosion of research on the intersection of machine learning and classical engineering domains. For example, machine learning is increasingly being used to develop ...

Differentiable Programming could open even more doors in HEP analysis and computing to Artificial Intelligence/Machine Learning. Current common uses of AI/ML in HEP are deep learning networks – ...

Optimal control is highly desirable in many current quantum systems, especially to realize tasks in quantum information processing. We introduce a method based on differentiable programming to ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Abstract: The notion of a Moreau envelope is central to the analysis of first-order optimization algorithms for machine learning and signal processing. We define a compositional calculus adapted to ...

Reduced models of transport necessarily have unknown closure relations which encode higher order physics; for example, the notorious flux limiter. In this work, we present a machine learning approach ...