Statistical Background Discrimination
Statistical Background Discrimination is a computational method in signal processing and data analysis that distinguishes target signals from background noise by leveraging statistical properties to enhance signal detectability against stochastic backgrounds.
17
Publications
440
Citations
61
Authors
31
Institutions
Publications per year
2017–2026
3
Parents
17
Privacy versus Antidiscrimination
Lior Strahilevitz · 2007 · 67 citations · Full text
Law, Criminology, Employment Law +17
Automating the ABCD method with machine learning
Gregor Kasieczka, Benjamin Nachman, Matthew D. Schwartz et al. · Physical review. D/Physical review. D. · 2021 · 58 citations · Full text
Computing, Computer Science, Physics +10
Dmitry Kalika, Mary Tai Knox, Leslie M. Collins et al. · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015 · 30 citations
1–5 of 17
61
Istituto Nazionale di Fisica Nucleare, Sezione di Roma I, Italy
1 publications · 20 citations
1
h-index
1
h-index
1
h-index
1
h-index
1
h-index
1–5 of 61
31
Universitat Politècnica de Catalunya
Barcelona, Spain
2 h-index
5 publications
67 citations

Rice University
Houston, United States
2 h-index
4 publications
73 citations
University of California, Irvine
Irvine, United States
2 h-index
4 publications
158 citations
NTT (Japan)
Tokyo, Japan
1 h-index
3 publications
72 citations
University of Oregon
Eugene, United States
1 h-index
1 publications
14 citations

Lawrence Berkeley National Laboratory
Berkeley, United States
1 h-index
2 publications
116 citations
Duke University
Durham, United States
1 h-index
5 publications
150 citations
University of Chicago
Chicago, United States
1 h-index
1 publications
67 citations
1–8 of 31
1 publications · 30 citations
1
h-index
Repository · 1 publications · 14 citations
1
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Conference · 1 publications · 24 citations
1
h-index
1 publications · 13 citations
1
h-index
1 publications · 49 citations
1
h-index
1–5