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Investigating Calibration and Corruption Robustness of Post-hoc Pruned
  Perception CNNs: An Image Classification Benchmark Study

Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study

31 May 2024
Pallavi Mitra
Gesina Schwalbe
Nadja Klein
    AAML
ArXiv (abs)PDFHTML

Papers citing "Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study"

48 / 48 papers shown
Title
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection
  Capability
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability
Jianing Zhu
Hengzhuang Li
Jiangchao Yao
Tongliang Liu
Jianliang Xu
Bo Han
OODD
80
13
0
06 Jun 2023
Pruning Compact ConvNets for Efficient Inference
Pruning Compact ConvNets for Efficient Inference
Sayan Ghosh
Karthik Prasad
Xiaoliang Dai
Peizhao Zhang
Bichen Wu
Graham Cormode
Peter Vajda
VLM
58
4
0
11 Jan 2023
A Comprehensive Survey on Model Quantization for Deep Neural Networks in
  Image Classification
A Comprehensive Survey on Model Quantization for Deep Neural Networks in Image Classification
Babak Rokh
A. Azarpeyvand
Alireza Khanteymoori
MQ
88
98
0
14 May 2022
Deadwooding: Robust Global Pruning for Deep Neural Networks
Deadwooding: Robust Global Pruning for Deep Neural Networks
Sawinder Kaur
Ferdinando Fioretto
Asif Salekin
66
4
0
10 Feb 2022
Membership Inference Attacks and Defenses in Neural Network Pruning
Membership Inference Attacks and Defenses in Neural Network Pruning
Xiaoyong Yuan
Lan Zhang
AAML
109
45
0
07 Feb 2022
Enabling Verification of Deep Neural Networks in Perception Tasks Using
  Fuzzy Logic and Concept Embeddings
Enabling Verification of Deep Neural Networks in Perception Tasks Using Fuzzy Logic and Concept Embeddings
Gesina Schwalbe
Christian Wirth
Ute Schmid
AAML
26
7
0
03 Jan 2022
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
301
940
0
21 Oct 2021
Sparse Deep Learning: A New Framework Immune to Local Traps and
  Miscalibration
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
Y. Sun
Wenjun Xiong
F. Liang
102
8
0
01 Oct 2021
On the Effect of Pruning on Adversarial Robustness
On the Effect of Pruning on Adversarial Robustness
Artur Jordão
Hélio Pedrini
AAML
91
23
0
10 Aug 2021
Revisiting the Calibration of Modern Neural Networks
Revisiting the Calibration of Modern Neural Networks
Matthias Minderer
Josip Djolonga
Rob Romijnders
F. Hubis
Xiaohua Zhai
N. Houlsby
Dustin Tran
Mario Lucic
UQCV
106
367
0
15 Jun 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A
  Systematic Survey of Surveys on Methods and Concepts
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts
Gesina Schwalbe
Bettina Finzel
XAI
92
196
0
15 May 2021
Network Pruning That Matters: A Case Study on Retraining Variants
Network Pruning That Matters: A Case Study on Retraining Variants
Duong H. Le
Binh-Son Hua
82
41
0
07 May 2021
Pruning and Quantization for Deep Neural Network Acceleration: A Survey
Pruning and Quantization for Deep Neural Network Acceleration: A Survey
Tailin Liang
C. Glossner
Lei Wang
Shaobo Shi
Xiaotong Zhang
MQ
229
700
0
24 Jan 2021
Strategy to Increase the Safety of a DNN-based Perception for HAD
  Systems
Strategy to Increase the Safety of a DNN-based Perception for HAD Systems
Timo Sämann
Peter Schlicht
Fabian Hüger
32
15
0
20 Feb 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep
  Learning in Safety-Critical Perception Tasks
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks
Oliver Willers
Sebastian Sudholt
Shervin Raafatnia
Stephanie Abrecht
90
80
0
22 Jan 2020
What Do Compressed Deep Neural Networks Forget?
What Do Compressed Deep Neural Networks Forget?
Sara Hooker
Aaron Courville
Gregory Clark
Yann N. Dauphin
Andrea Frome
89
185
0
13 Nov 2019
High Fidelity Video Prediction with Large Stochastic Recurrent Neural
  Networks
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks
Ruben Villegas
Arkanath Pathak
Harini Kannan
D. Erhan
Quoc V. Le
Honglak Lee
VGen
66
139
0
05 Nov 2019
CARS: Continuous Evolution for Efficient Neural Architecture Search
CARS: Continuous Evolution for Efficient Neural Architecture Search
Zhaohui Yang
Yunhe Wang
Xinghao Chen
Boxin Shi
Chao Xu
Chunjing Xu
Qi Tian
Chang Xu
102
228
0
11 Sep 2019
Benchmarking Robustness in Object Detection: Autonomous Driving when
  Winter is Coming
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
Claudio Michaelis
Benjamin Mitzkus
Robert Geirhos
E. Rusak
Oliver Bringmann
Alexander S. Ecker
Matthias Bethge
Wieland Brendel
3DPC
103
452
0
17 Jul 2019
Importance Estimation for Neural Network Pruning
Importance Estimation for Neural Network Pruning
Pavlo Molchanov
Arun Mallya
Stephen Tyree
I. Frosio
Jan Kautz
3DPC
89
885
0
25 Jun 2019
Adversarially Robust Distillation
Adversarially Robust Distillation
Micah Goldblum
Liam H. Fowl
Soheil Feizi
Tom Goldstein
AAML
78
210
0
23 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and
  Perturbations
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks
Thomas G. Dietterich
OODVLM
194
3,455
0
28 Mar 2019
Model Compression with Adversarial Robustness: A Unified Optimization
  Framework
Model Compression with Adversarial Robustness: A Unified Optimization Framework
Shupeng Gui
Haotao Wang
Chen Yu
Haichuan Yang
Zhangyang Wang
Ji Liu
MQ
65
138
0
10 Feb 2019
Really should we pruning after model be totally trained? Pruning based
  on a small amount of training
Really should we pruning after model be totally trained? Pruning based on a small amount of training
Li Yue
Zhao Weibin
Shang-Te Lin
VLM
29
5
0
24 Jan 2019
Sparse DNNs with Improved Adversarial Robustness
Sparse DNNs with Improved Adversarial Robustness
Yiwen Guo
Chao Zhang
Changshui Zhang
Yurong Chen
AAML
86
154
0
23 Oct 2018
Rethinking the Value of Network Pruning
Rethinking the Value of Network Pruning
Zhuang Liu
Mingjie Sun
Tinghui Zhou
Gao Huang
Trevor Darrell
40
1,475
0
11 Oct 2018
SNIP: Single-shot Network Pruning based on Connection Sensitivity
SNIP: Single-shot Network Pruning based on Connection Sensitivity
Namhoon Lee
Thalaiyasingam Ajanthan
Philip Torr
VLM
269
1,211
0
04 Oct 2018
Object Detection with Deep Learning: A Review
Object Detection with Deep Learning: A Review
Zhong-Qiu Zhao
Peng Zheng
Shou-tao Xu
Xindong Wu
ObjD
134
4,017
0
15 Jul 2018
Benchmarking Neural Network Robustness to Common Corruptions and Surface
  Variations
Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations
Dan Hendrycks
Thomas G. Dietterich
OOD
84
202
0
04 Jul 2018
Towards Dependability Metrics for Neural Networks
Towards Dependability Metrics for Neural Networks
Chih-Hong Cheng
Georg Nührenberg
Chung-Hao Huang
Harald Ruess
Hirotoshi Yasuoka
55
44
0
06 Jun 2018
Why do deep convolutional networks generalize so poorly to small image
  transformations?
Why do deep convolutional networks generalize so poorly to small image transformations?
Aharon Azulay
Yair Weiss
82
562
0
30 May 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle
Michael Carbin
272
3,488
0
09 Mar 2018
AMC: AutoML for Model Compression and Acceleration on Mobile Devices
AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Yihui He
Ji Lin
Zhijian Liu
Hanrui Wang
Li Li
Song Han
100
1,349
0
10 Feb 2018
To prune, or not to prune: exploring the efficacy of pruning for model
  compression
To prune, or not to prune: exploring the efficacy of pruning for model compression
Michael Zhu
Suyog Gupta
197
1,282
0
05 Oct 2017
Learning Efficient Convolutional Networks through Network Slimming
Learning Efficient Convolutional Networks through Network Slimming
Zhuang Liu
Jianguo Li
Zhiqiang Shen
Gao Huang
Shoumeng Yan
Changshui Zhang
130
2,426
0
22 Aug 2017
Channel Pruning for Accelerating Very Deep Neural Networks
Channel Pruning for Accelerating Very Deep Neural Networks
Yihui He
Xiangyu Zhang
Jian Sun
206
2,531
0
19 Jul 2017
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
299
5,871
0
14 Jun 2017
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
195
3,707
0
31 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
282
8,587
0
16 Aug 2016
Concrete Problems in AI Safety
Concrete Problems in AI Safety
Dario Amodei
C. Olah
Jacob Steinhardt
Paul Christiano
John Schulman
Dandelion Mané
253
2,405
0
21 Jun 2016
End to End Learning for Self-Driving Cars
End to End Learning for Self-Driving Cars
Mariusz Bojarski
D. Testa
Daniel Dworakowski
Bernhard Firner
B. Flepp
...
Urs Muller
Jiakai Zhang
Xin Zhang
Jake Zhao
Karol Zieba
SSL
102
4,178
0
25 Apr 2016
Understanding How Image Quality Affects Deep Neural Networks
Understanding How Image Quality Affects Deep Neural Networks
Samuel F. Dodge
Lina Karam
VLM
85
732
0
14 Apr 2016
EIE: Efficient Inference Engine on Compressed Deep Neural Network
EIE: Efficient Inference Engine on Compressed Deep Neural Network
Song Han
Xingyu Liu
Huizi Mao
Jing Pu
A. Pedram
M. Horowitz
W. Dally
132
2,461
0
04 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,510
0
10 Dec 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained
  Quantization and Huffman Coding
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han
Huizi Mao
W. Dally
3DGS
263
8,862
0
01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks
Learning both Weights and Connections for Efficient Neural Networks
Song Han
Jeff Pool
J. Tran
W. Dally
CVBM
316
6,709
0
08 Jun 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,529
0
04 Sep 2014
Exploiting Linear Structure Within Convolutional Networks for Efficient
  Evaluation
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
Emily L. Denton
Wojciech Zaremba
Joan Bruna
Yann LeCun
Rob Fergus
FAtt
179
1,693
0
02 Apr 2014
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