activity
20162021
most citedEnabling particle applications for exascale computing platforms

29 citations · 29 across the 2 of their papers we have counts for

collaborators

5 papers

cs.DC202129 cited

Enabling particle applications for exascale computing platforms

Susan M Mniszewski, James Belak, Jean-Luc Fattebert +21

The Exascale Computing Project (ECP) is invested in co-design to assure that key applications are ready for exascale computing. Within ECP, the Co-design Center for Particle Applic…

cs.PF2021

Performance Optimizations of Recursive Electronic Structure Solvers targeting Multi-Core Architectures (LA-UR-20-26665)

Adetokunbo A. Adedoyin, Christian F. A. Negre, Jamaludin Mohd-Yusof +6

As we rapidly approach the frontiers of ultra large computing resources, software optimization is becoming of paramount interest to scientific application developers interested in…

stat.ML2019

Combating Label Noise in Deep Learning Using Abstention

Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes +2

We introduce a novel method to combat label noise when training deep neural networks for classification. We propose a loss function that permits abstention during training thereby…

physics.geo-ph2018

Earthquake catalog-based machine learning identification of laboratory fault states and the effects of magnitude of completeness

Nicholas Lubbers, David C. Bolton, Jamaludin Mohd-Yusof +3

Machine learning regression can predict macroscopic fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions.…

physics.comp-ph2016

Graph-based linear scaling electronic structure theory

Anders M. N. Niklasson, Susan M. Mniszewski, Christian F. A. Negre +8

We show how graph theory can be combined with quantum theory to calculate the electronic structure of large complex systems. The graph formalism is general and applicable to a broa…