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Physics Community Needs, Tools, and Resources for Machine Learning

Physics Community Needs, Tools, and Resources for Machine Learning

Philip C. Harris
E. Katsavounidis
W. McCormack
D. Rankin
Yongbin Feng
A. Gandrakota
C. Herwig
B. Holzman
K. Pedro
Nhan Tran
Tingjun Yang
J. Ngadiuba
Michael W. Coughlin
Scott Hauck
Shih-Chieh Hsu
Elham E Khoda
De-huai Chen
Mark S. Neubauer
Javier Mauricio Duarte
G. Karagiorgi
Miaoyuan Liu
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Papers citing "Physics Community Needs, Tools, and Resources for Machine Learning"

2 / 2 papers shown
Title
Fast inference of deep neural networks in FPGAs for particle physics
Fast inference of deep neural networks in FPGAs for particle physics
Javier Mauricio Duarte
Song Han
Philip C. Harris
S. Jindariani
E. Kreinar
...
J. Ngadiuba
M. Pierini
R. Rivera
N. Tran
Zhenbin Wu
AI4CE
77
387
0
16 Apr 2018
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks
Evan Racah
Seyoon Ko
Peter Sadowski
W. Bhimji
C. Tull
Sang-Yun Oh
Pierre Baldi
P. Prabhat
40
32
0
28 Jan 2016