Point Process Filtering
Point Process Filtering is a statistical inference method that belongs to the class of filtering techniques for stochastic processes, specifically distinguished by its application to estimate the latent intensity or state of a point process given observed event times up to the current time.
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2.8K
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115
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69
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2017–2026
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Dynamic Analysis of Neural Encoding by Point Process Adaptive Filtering
Uri T. Eden, Loren M. Frank, Riccardo Barbieri et al. · Neural Computation · 2004 · 366 citations
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Boston University
Boston, United States
4 h-index
7 publications
253 citations
Massachusetts Institute of Technology
Cambridge, United States
4 h-index
10 publications
1.9K citations
Massachusetts General Hospital
Boston, United States
4 h-index
13 publications
2.4K citations
University of California, San Francisco
San Francisco, United States
3 h-index
6 publications
304 citations
University of Southern California
Los Angeles, United States
3 h-index
5 publications
254 citations
University of California, Berkeley
Berkeley, United States
2 h-index
4 publications
408 citations
University of Florida
Gainesville, United States
2 h-index
8 publications
248 citations
Université de Rennes
Rennes, France
2 h-index
2 publications
155 citations
1–8 of 69
4 publications · 126 citations
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3 publications · 227 citations
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3 publications · 459 citations
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AAP · 2 publications · 155 citations
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2 publications · 40 citations
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