QuantTPM: Efficient Mixed-Precision Quantization Framework for Tractable Probabilistic Models

Authors

Guangyao Yan (ORCID: https://orcid.org/0000-0002-8256-7435)
Xinzhe Liu (ORCID: https://orcid.org/0000-0002-7557-4960)
Baiqi Ning (ORCID: https://orcid.org/0000-0001-6259-0497)
Weixiong Jiang (ORCID: https://orcid.org/0000-0002-6014-6453)
Yajun Ha (ORCID: https://orcid.org/0000-0003-4244-5916)
Shen Zhang (ORCID: https://orcid.org/0000-0002-1245-0565)

Institutions

ShanghaiTech University (CN)

Publication Details

Journal: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Published: 2025-02-18
DOI: https://doi.org/10.1109/tcad.2025.3543424
Primary Topic: Image Retrieval and Classification Techniques
Type: article
Field-Weighted Citation Impact: 0.00

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article

QuantTPM: Efficient Mixed-Precision Quantization Framework for Tractable Probabilistic Models

Guangyao Yan, Xinzhe Liu, Baiqi Ning, Weixiong Jiang et al.

Feb 18, 2025

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Image Retrieval and Classification Techniques

article

QuantTPM: Efficient Mixed-Precision Quantization Framework for Tractable Probabilistic Models

Guangyao Yan, Xinzhe Liu, Baiqi Ning, Weixiong Jiang, Yajun Ha, Shen Zhang

February 18, 2025article en

Abstract

No abstract available for this paper.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsVol. 44(9)

ShanghaiTech University (CN)

Openalex Percentile: Top 98%

Image Retrieval and Classification Techniques

DOI Source OpenAlex

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