Point Process Inference
Point Process Inference is a statistical inference framework that, as a subclass of probabilistic modeling methods, specifically involves estimating the underlying intensity function, structure, or parameters of a point process from observed event data in continuous space or time.
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4K
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125
Authors
71
Institutions
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2017–2026
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University of Oxford
Oxford, United Kingdom
4 h-index
14 publications
416 citations
Aalborg University
Aalborg, Denmark
4 h-index
5 publications
355 citations
University of California, Los Angeles
Los Angeles, United States
3 h-index
4 publications
400 citations
Duke University
Durham, United States
3 h-index
7 publications
121 citations

UNSW Sydney
Sydney, Australia
2 h-index
3 publications
652 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
2 h-index
4 publications
322 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
2 h-index
5 publications
55 citations

Pennsylvania State University
State College, United States
2 h-index
4 publications
618 citations
1–8 of 71
Repository · 5 publications · 140 citations
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4 publications · 667 citations
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4 publications · 634 citations
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2 publications · 270 citations
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AAP · 2 publications · 44 citations
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