Probabilistic Refinement
Probabilistic Refinement is a refinement calculus framework that extends classical refinement relations with probabilistic choice, enabling the formal derivation of probabilistic programs by preserving safety and liveness properties under stochastic behavior.
12
Publications
210
Citations
62
Authors
37
Institutions
Publications per year
2017–2026
1
Parents
12
Optimizing selection of competing services with probabilistic hierarchical refinement
Tian Tan, Manman Chen, Jun Sun et al. · 2016 · 23 citations · Full text
A Flexible Online Camera Calibration Using Line Segments
Yueqiang Zhang, Langming Zhou, Haibo Liu et al. · Journal of Sensors · 2016 · 16 citations · Full text
1–5 of 12
62
1
h-index
1
h-index
Swiss Tropical and Public Health Institute, Switzerland
1 publications · 23 citations
1
h-index
1
h-index
1
h-index
1–5 of 62
37
Turku Centre for Computer Science
Turku, Finland
2 h-index
2 publications
29 citations
Åbo Akademi University
Turku, Finland
2 h-index
2 publications
29 citations

Universidad Nacional de Córdoba
Córdoba, Argentina
1 h-index
1 publications
10 citations
Ministry of Health
Nicosia, Cyprus
1 h-index
1 publications
23 citations
Federal Institute for Risk Assessment
Berlin, Germany
1 h-index
1 publications
23 citations
Israel Ministry of Health
Jerusalem, Israel
1 h-index
1 publications
23 citations
National Institute of Health Dr. Ricardo Jorge
Lisbon, Portugal
1 h-index
1 publications
23 citations
Finnish Institute of Occupational Health
Helsinki, Finland
1 h-index
1 publications
23 citations
1–8 of 37
2 publications · 29 citations
2
h-index
1 publications · 10 citations
1
h-index
Conference · 1 publications · 11 citations
1
h-index
1 publications · 16 citations
1
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ENTCS · 1 publications · 13 citations
1
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1–5