Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning

Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning

18 December 2019

Sebastian Lapuschkin

Alexander Binder

Simon Wiedemann

Papers citing "Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning"

19 / 19 papers shown

Title
Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation Paulo Yanez Sarmiento Simon Witzke Nadja Klein Bernhard Y. Renard FAtt AAML 40 0 0 22 Apr 2024
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation Yun-Wei Chu Dong-Jun Han Christopher G. Brinton 28 4 0 15 Jan 2024
PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs Max Zimmer Megi Andoni Christoph Spiegel Sebastian Pokutta VLM 52 10 0 23 Dec 2023
On the Relationship Between Interpretability and Explainability in Machine Learning Benjamin Leblanc Pascal Germain FaML 29 0 0 20 Nov 2023
A Novel Correlation-optimized Deep Learning Method for Wind Speed Forecast Yang Yang Jin Lang Jian Wu Yanyan Zhang Xiangman Song 27 7 0 03 Jun 2023
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks Lorenz Linhardt Klaus-Robert Muller G. Montavon AAML 26 7 0 12 Apr 2023
Less is More: The Influence of Pruning on the Explainability of CNNs David Weber F. Merkle Pascal Schöttle Stephan Schlögl Martin Nocker FAtt 34 1 0 17 Feb 2023
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces Pattarawat Chormai J. Herrmann Klaus-Robert Muller G. Montavon FAtt 48 17 0 30 Dec 2022
Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine A. Chaddad Qizong Lu Jiali Li Y. Katib R. Kateb C. Tanougast Ahmed Bouridane Ahmed Abdulkadir OOD 24 38 0 17 Nov 2022
Automating the Design and Development of Gradient Descent Trained Expert System Networks Jeremy Straub 26 9 0 04 Jul 2022
Cut Inner Layers: A Structured Pruning Strategy for Efficient U-Net GANs Bo-Kyeong Kim Shinkook Choi Hancheol Park 18 4 0 29 Jun 2022
Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI Sami Ede Serop Baghdadlian Leander Weber A. Nguyen Dario Zanca Wojciech Samek Sebastian Lapuschkin CLL 27 6 0 04 May 2022
LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification Sharath Girish Kamal Gupta Saurabh Singh Abhinav Shrivastava 36 11 0 06 Apr 2022
Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy Thibault Castells Seul-Ki Yeom 3DV 18 3 0 18 Nov 2021
S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based Networks Shiyu Liu Chong Min John Tan Mehul Motani CLL 29 4 0 17 Oct 2021
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy Christopher J. Anders David Neumann Wojciech Samek K. Müller Sebastian Lapuschkin 29 64 0 24 Jun 2021
Toward Compact Deep Neural Networks via Energy-Aware Pruning Seul-Ki Yeom Kyung-Hwan Shim Jee-Hyun Hwang CVBM 28 12 0 19 Mar 2021
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI L. Arras Ahmed Osman Wojciech Samek XAI AAML 21 150 0 16 Mar 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017