Research paper / RESOURCE PROFILE

ICML 2021

Publication: HAWQV3: Dyadic Neural Network Quantization. Published Nov 20, 2020.

Research & Papers
arxiv.orgPublished Nov 20, 2020
Visit source website ↗

Overview

Publication: HAWQV3: Dyadic Neural Network Quantization. Published Nov 20, 2020.

Publication information

Publication title
HAWQV3: Dyadic Neural Network Quantization
Authors
Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael W. Mahoney, Kurt Keutzer
Published
Nov 20, 2020
Last publication revision
Jun 23, 2021
Venue / journal
ICML 2021
Subject areas
cs.CV
Publication source
arxiv.org · abs/2011.10680v3 ↗

Source: arXiv API · observed Oct 11, 2026.

Source links & provenance

https://arxiv.org/abs/2011.10680 ↗

Discovery references

References explain how this resource entered the collection. They do not represent an endorsement.

Explore related resources

Screenshot unavailableResource information and source links remain available. DeepIntoStreams/TSFM_Finance — reviewed source website screenshot
RepositoryChecked capture

DeepIntoStreams/TSFM_Finance

github.com

the official implementation of the paper “Re(visiting) Time Series Foundation Models in Finance”.

GitHub stars
31
Language
Jupyter Notebook
Code license
Apache-2.0
foundation-modeltime-seriesresearch-lab
Research & Papers Explore →
96 Authority 96 / 100 Cited by 2 resources in this directory 2 discovery sources Directory record updated: 2026-10-11 How scoring works →

Sign In

Don't have an account yet? Register

Forgot password?

Register

Reset Password

Please enter your username or email address, you will receive a link to create a new password via email.