Publications (20)
Lifelong Learning Metrics
Alexander New, Megan Baker, Eric Nguyen +1
The DARPA Lifelong Learning Machines (L2M) program seeks to yield advances in artificial intelligence (AI) systems so that they are capable of learning (and improving) continuously…
L2Explorer: A Lifelong Reinforcement Learning Assessment Environment
Erik C. Johnson, Eric Q. Nguyen, Blake Schreurs +6
Despite groundbreaking progress in reinforcement learning for robotics, gameplay, and other complex domains, major challenges remain in applying reinforcement learning to the evolv…
Closed-loop machine learning for discovery of novel superconductors
Elizabeth A. Pogue, Alexander New, Kyle McElroy +15
The discovery of novel materials drives industrial innovation, although the pace of discovery tends to be slow due to the infrequency of "Eureka!" moments. These moments are typica…
Cadre Modeling: Simultaneously Discovering Subpopulations and Predictive Models
Alexander New, Curt Breneman, Kristin P. Bennett
We consider the problem in regression analysis of identifying subpopulations that exhibit different patterns of response, where each subpopulation requires a different underlying m…
Data-efficient operator learning for solving high Mach number fluid flow problems
Noah Ford, Victor J. Leon, Honest Mrema +2
We consider the problem of using SciML to predict solutions of high Mach fluid flows over irregular geometries. In this setting, data is limited, and so it is desirable for models…
A Precision Environment-Wide Association Study of Hypertension via Supervised Cadre Models
Alexander New, Kristin P. Bennett
We consider the problem in precision health of grouping people into subpopulations based on their degree of vulnerability to a risk factor. These subpopulations cannot be discovere…