Structurally Prune Anything: Any Architecture, Any Framework, Any Time

Structurally Prune Anything: Any Architecture, Any Framework, Any Time

3 March 2024

Stephan Günnemann

Bertrand Charpentier

Papers citing "Structurally Prune Anything: Any Architecture, Any Framework, Any Time"

10 / 10 papers shown

Title
HESSO: Towards Automatic Efficient and User Friendly Any Neural Network Training and Pruning Tianyi Chen Xiaoyi Qu David Aponte Colby R. Banbury Jongwoo Ko Tianyu Ding Yong Ma Vladimir Lyapunov Ilya Zharkov Luming Liang 70 1 0 11 Sep 2024
Predicting Probabilities of Error to Combine Quantization and Early Exiting: QuEE Florence Regol Joud Chataoui Bertrand Charpentier Mark J. Coates Pablo Piantanida Stephan Gunnemann 30 0 0 20 Jun 2024
ONNXPruner: ONNX-Based General Model Pruning Adapter Dongdong Ren Wenbin Li Tianyu Ding Lei Wang Qi Fan Jing Huo Hongbing Pan Yang Gao 27 3 0 10 Apr 2024
OTOV2: Automatic, Generic, User-Friendly Tianyi Chen Luming Liang Tian Ding Zhihui Zhu Ilya Zharkov VLM MQ 35 30 0 13 Mar 2023
DepGraph: Towards Any Structural Pruning Gongfan Fang Xinyin Ma Mingli Song Michael Bi Mi Xinchao Wang GNN 79 245 0 30 Jan 2023
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 178 1,018 0 06 Mar 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,927 0 20 Apr 2018
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,214 0 17 Apr 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,106 0 16 Nov 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 244 35,884 0 25 Aug 2016