Cache Inference Models
Cache Inference Models is a computational framework that integrates caching mechanisms with probabilistic inference to optimize the reuse of previously computed results in machine learning pipelines by dynamically predicting and retrieving high-value intermediate representations.
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Publications
307
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23
Authors
9
Institutions
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2017–2026
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The University of Sydney
Sydney, Australia
1 h-index
1 publications
173 citations

University of Twente
Enschede, The Netherlands
1 h-index
1 publications
19 citations
TU Dortmund University
Dortmund, Germany
1 h-index
4 publications
76 citations
University of Lay Adventists of Kigali
Kigali, Rwanda
1 h-index
1 publications
173 citations
Kyung Hee University
Seoul, South Korea
1 h-index
4 publications
692 citations
Microsoft (United States)
Redmond, United States
1 h-index
3 publications
126 citations
National Tsing Hua University
Hsinchu, Taiwan
1 h-index
3 publications
57 citations
University of Technology Malaysia
Johor Bahru, Malaysia
1 h-index
3 publications
141 citations
1–8 of 9
TECS · 1 publications · 19 citations
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1 publications · 173 citations
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1 publications · 47 citations
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Repository · 1 publications · 10 citations
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