81 citations · 91 across the 4 of their papers we have counts for
9 papers
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems
Steven Farrell, Murali Emani, Jacob Balma +40
Scientific communities are increasingly adopting machine learning and deep learning models in their applications to accelerate scientific insights. High performance computing syste…
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads
Aymen Al Saadi, Dario Alfe, Yadu Babuji +33
The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive…
FPGA-accelerated machine learning inference as a service for particle physics computing
Javier Duarte, Philip Harris, Scott Hauck +20
New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large pote…
Measurement of Neutrino-Induced Neutral-Current Coherent Production in the NOvA Near Detector
M. A. Acero, P. Adamson, L. Aliaga +188
The cross section of neutrino-induced neutral-current coherent production on a carbon-dominated target is measured in the NOvA near detector. This measurement uses a narrow-b…
Novel deep learning methods for track reconstruction
Steven Farrell, Paolo Calafiura, Mayur Mudigonda +11
For the past year, the HEP.TrkX project has been investigating machine learning solutions to LHC particle track reconstruction problems. A variety of models were studied that drew…
New constraints on oscillation parameters from appearance and disappearance in the NOvA experiment
M. A. Acero, P. Adamson, L. Aliaga T. Alion +126
We present updated results from the NOvA experiment for and oscillations from an exposure of protons on target, which re…