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SUMMARY:Probabilistic inference using contraction of tensor networks - Mar
 tin Roa-Villescas
DTSTART;TZID=Europe/Amsterdam:20240710T140000
DTEND;TZID=Europe/Amsterdam:20240710T143000
DTSTAMP:20260818T164114Z
UID:pretalx-juliacon2024-HTCDFD@pretalx.com
DESCRIPTION:TensorInference\, a package for exact probabilistic inference 
 in discrete graphical models\, capitalizes on recent tensor network advanc
 ements. Its tensor-based engine features optimized contraction ordering me
 thods\, an aspect vital to computational performance. Additionally\, it in
 corporates optimized BLAS routines and GPU technology for enhanced efficie
 ncy. In a comparative evaluation with similar libraries\, TensorInference 
 demonstrates superior scalability for models of increasing complexity.
LOCATION:Method (1.5)
URL:https://pretalx.com/juliacon2024/talk/HTCDFD/
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