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ProbLP: A framework for low-precision probabilistic inference

ProbLP: A framework for low-precision probabilistic inference

27 February 2021
Nimish Shah
Laura Isabel Galindez Olascoaga
Wannes Meert
Marian Verhelst
ArXiv (abs)PDFHTML

Papers citing "ProbLP: A framework for low-precision probabilistic inference"

4 / 4 papers shown
Title
On Hardware-efficient Inference in Probabilistic Circuits
On Hardware-efficient Inference in Probabilistic Circuits
Lingyun Yao
Martin Trapp
Jelin Leslin
Gaurav Singh
Peng Zhang
Karthekeyan Periasamy
M. Andraud
TPM
86
0
0
22 May 2024
DPU: DAG Processing Unit for Irregular Graphs with Precision-Scalable
  Posit Arithmetic in 28nm
DPU: DAG Processing Unit for Irregular Graphs with Precision-Scalable Posit Arithmetic in 28nm
Nimish Shah
Laura Isabel Galindez Olascoaga
Shirui Zhao
Wannes Meert
Marian Verhelst
46
12
0
10 Dec 2021
Acceleration of probabilistic reasoning through custom processor
  architecture
Acceleration of probabilistic reasoning through custom processor architecture
Nimish Shah
Laura Isabel Galindez Olascoaga
Wannes Meert
Marian Verhelst
BDL
22
12
0
27 Feb 2021
Monte Carlo Anti-Differentiation for Approximate Weighted Model
  Integration
Monte Carlo Anti-Differentiation for Approximate Weighted Model Integration
Pedro Zuidberg Dos Martires
Samuel Kolb
TPM
43
2
0
13 Jan 2020
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