ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2003.00631
  4. Cited By
Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism
  Principled Robust Deep Neural Nets

Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets

2 March 2020
Thu Dinh
Bao Wang
Andrea L. Bertozzi
Stanley J. Osher
    AAML
ArXivPDFHTML

Papers citing "Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets"

3 / 3 papers shown
Title
glassoformer: a query-sparse transformer for post-fault power grid
  voltage prediction
glassoformer: a query-sparse transformer for post-fault power grid voltage prediction
Yunling Zheng
Carson Hu
Guang Lin
Meng Yue
Bao Wang
Jack Xin
70
2
0
22 Jan 2022
On the Convergence and Robustness of Adversarial Training
On the Convergence and Robustness of Adversarial Training
Yisen Wang
Xingjun Ma
James Bailey
Jinfeng Yi
Bowen Zhou
Quanquan Gu
AAML
194
345
0
15 Dec 2021
Incremental Network Quantization: Towards Lossless CNNs with
  Low-Precision Weights
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights
Aojun Zhou
Anbang Yao
Yiwen Guo
Lin Xu
Yurong Chen
MQ
337
1,049
0
10 Feb 2017
1