Probabilistic Multi-task Learning
Probabilistic Multi-Task Learning is a multi-task learning framework that belongs to the class of probabilistic models by explicitly modeling task relationships and uncertainties through joint probability distributions over outputs and latent task structures.
35
Publications
1.8K
Citations
117
Authors
64
Institutions
Publications per year
2017–2026
15
Parents
35
James F. Cavanagh, Andrew W. Bismark, Michael J. Frank et al. · Computational Psychiatry · 2018 · 139 citations · Full text
Nursing, Psychiatry, Psychology +16
Probabilistic learning of task-specific visual attention
Ali Borji, Dicky N. Sihite, Laurent Itti · 2012 · 121 citations
1–5 of 35
117
Hong Kong University of Science and Technology, Hong Kong SAR China
2 publications · 122 citations
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Hong Kong University of Science and Technology, Hong Kong SAR China
2 publications · 122 citations
2
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1
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1
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1–5 of 117
64
University of Cambridge
Cambridge, United Kingdom
2 h-index
6 publications
529 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
2 h-index
4 publications
300 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
7 publications
488 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
2 h-index
4 publications
300 citations
University College London
London, United Kingdom
2 h-index
4 publications
230 citations
Jesse Brown VA Medical Center
Chicago, United States
1 h-index
4 publications
132 citations
Hong Kong Baptist University
Hong Kong, Hong Kong
1 h-index
1 publications
33 citations

Radboud University Nijmegen
Nijmegen, The Netherlands
1 h-index
1 publications
47 citations
1–8 of 64
Repository · 4 publications · 132 citations
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2 publications · 36 citations
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TKDE · 1 publications · 31 citations
1
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1 publications · 30 citations
1
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1 publications · 19 citations
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