17 citations · 17 across the 4 of their papers we have counts for
4 papers · 1 filter
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Megan M. Baker, Alexander New, Mario Aguilar-Simon +44
Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks enc…
Neural Basis Functions for Accelerating Solutions to High Mach Euler Equations
David Witman, Alexander New, Hicham Alkendry +1
We propose an approach to solving partial differential equations (PDEs) using a set of neural networks which we call Neural Basis Functions (NBF). This NBF framework is a novel var…
Curvature-informed multi-task learning for graph networks
Alexander New, Michael J. Pekala, Nam Q. Le +3
Properties of interest for crystals and molecules, such as band gap, elasticity, and solubility, are generally related to each other: they are governed by the same underlying laws…
Latent Properties of Lifelong Learning Systems
Corban Rivera, Chace Ashcraft, Alexander New +2
Creating artificial intelligence (AI) systems capable of demonstrating lifelong learning is a fundamental challenge, and many approaches and metrics have been proposed to analyze a…