English

CupNet -- Pruning a network for geometric data

Machine Learning 2021-09-14 v2 Machine Learning
Authors: Raoul Heese , Lukas Morand , Dirk Helm , Michael Bortz
View on arXiv ↗ PDF ↗ DOI ↗

Abstract

Using data from a simulated cup drawing process, we demonstrate how the inherent geometrical structure of cup meshes can be used to effectively prune an artificial neural network in a straightforward way.

Keywords

mesh generation complex network analysis geometric modeling

Cite

@article{arxiv.2005.05276,
  title  = {CupNet -- Pruning a network for geometric data},
  author = {Raoul Heese and Lukas Morand and Dirk Helm and Michael Bortz},
  journal= {arXiv preprint arXiv:2005.05276},
  year   = {2021}
}

Comments

4 pages, 2 figures, 1 table

Related papers

View all related →
Machine Learning · Statistics
A Closer Look at Structured Pruning for Neural Network Compression
Elliot J. Crowley, Jack Turner, Amos Storkey, Michael O'Boyle
2019-06-10
Computer Vision and Pattern Recognition · Computer Science
CUP: Cluster Pruning for Compressing Deep Neural Networks
Rahul Duggal, Cao Xiao, Richard Vuduc, Jimeng Sun
2019-11-21
Neural and Evolutionary Computing · Computer Science
Leveraging Structured Pruning of Convolutional Neural Networks
Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel +2
2022-12-13
Machine Learning · Computer Science
Adaptive Pruning of Deep Neural Networks for Resource-Aware Embedded Intrusion Detection on the Edge
Alexandre Broggi, Nathaniel Bastian, Lance Fiondella, Gokhan Kul
2025-05-21
Computer Vision and Pattern Recognition · Computer Science
Pruning from Scratch
Yulong Wang, Xiaolu Zhang, Lingxi Xie, Jun Zhou +3
2019-09-30
Computer Vision and Pattern Recognition · Computer Science
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning
Zechun Liu, Haoyuan Mu, Xiangyu Zhang, Zichao Guo +3
2019-08-15
Machine Learning · Computer Science
Meta Pruning via Graph Metanetworks : A Universal Meta Learning Framework for Network Pruning
Yewei Liu, Xiyuan Wang, Muhan Zhang
2025-12-16
Machine Learning · Computer Science
Quantisation and Pruning for Neural Network Compression and Regularisation
Kimessha Paupamah, Steven James, Richard Klein
2020-01-15
Computer Vision and Pattern Recognition · Computer Science
Network Automatic Pruning: Start NAP and Take a Nap
Wenyuan Zeng, Yuwen Xiong, Raquel Urtasun
2021-01-19
Computer Vision and Pattern Recognition · Computer Science
Structured Pruning for Deep Convolutional Neural Networks: A survey
Yang He, Lingao Xiao
2023-12-01
Machine Learning · Statistics
Pruning a neural network using Bayesian inference
Sunil Mathew, Daniel B. Rowe
2023-08-07
Machine Learning · Computer Science
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy
Lucas Liebenwein, Cenk Baykal, Brandon Carter, David Gifford +1
2021-03-05
Machine Learning · Computer Science
A Framework for Neural Network Pruning Using Gibbs Distributions
Alex Labach, Shahrokh Valaee
2021-12-30
Computer Vision and Pattern Recognition · Computer Science
Towards thinner convolutional neural networks through Gradually Global Pruning
Zhengtao Wang, Ce Zhu, Zhiqiang Xia, Qi Guo +1
2017-03-30
Hardware Architecture · Computer Science
FPGA Resource-aware Structured Pruning for Real-Time Neural Networks
Benjamin Ramhorst, Vladimir Loncar, George A. Constantinides
2025-04-21
Machine Learning · Computer Science
Data-Efficient Structured Pruning via Submodular Optimization
Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
2023-02-14
Machine Learning · Computer Science
Deep Neural Networks pruning via the Structured Perspective Regularization
Matteo Cacciola, Antonio Frangioni, Xinlin Li, Andrea Lodi
2022-06-29
Machine Learning · Computer Science
Dissecting Pruned Neural Networks
Jonathan Frankle, David Bau
2019-07-02
Computer Vision and Pattern Recognition · Computer Science
Neural Network Pruning Through Constrained Reinforcement Learning
Shehryar Malik, Muhammad Umair Haider, Omer Iqbal, Murtaza Taj
2021-11-01
Machine Learning · Computer Science
SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks
Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman +1
2021-03-16
Machine Learning · Computer Science
Effective Network Compression Using Simulation-Guided Iterative Pruning
Dae-Woong Jeong, Jaehun Kim, Youngseok Kim, Tae-Ho Kim +1
2019-02-13
Machine Learning · Computer Science
Weight Pruning via Adaptive Sparsity Loss
George Retsinas, Athena Elafrou, Georgios Goumas, Petros Maragos
2020-06-05
Machine Learning · Computer Science
Neural Network Panning: Screening the Optimal Sparse Network Before Training
Xiatao Kang, Ping Li, Jiayi Yao, Chengxi Li
2022-09-28
Machine Learning · Computer Science
Pruning neural network models for gene regulatory dynamics using data and domain knowledge
Intekhab Hossain, Jonas Fischer, Rebekka Burkholz, John Quackenbush
2024-10-29
Machine Learning · Computer Science
Data-Independent Structured Pruning of Neural Networks via Coresets
Ben Mussay, Daniel Feldman, Samson Zhou, Vladimir Braverman +1
2020-08-21
R2 v1 2026-06-23T15:27:54.656Z