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On the uncertainty principle of neural networks

On the uncertainty principle of neural networks

17 January 2025
Jun-Jie Zhang
Dong-xiao Zhang
Jian-Nan Chen
L. Pang
Deyu Meng
ArXivPDFHTML

Papers citing "On the uncertainty principle of neural networks"

39 / 39 papers shown
Title
Is AI Robust Enough for Scientific Research?
Is AI Robust Enough for Scientific Research?
Jun-Jie Zhang
Jiahao Song
Xiu-Cheng Wang
Fu-Peng Li
Zehan Liu
...
L. Pang
Nan Cheng
Weiwei Zhang
Duo Zhang
Deyu Meng
80
1
0
19 Dec 2024
A Systematic Evaluation of Adversarial Attacks against Speech Emotion
  Recognition Models
A Systematic Evaluation of Adversarial Attacks against Speech Emotion Recognition Models
Nicolas Facchinetti
Federico Simonetta
Stavros Ntalampiras
AAML
20
1
0
29 Apr 2024
Quantum-Inspired Analysis of Neural Network Vulnerabilities: The Role of
  Conjugate Variables in System Attacks
Quantum-Inspired Analysis of Neural Network Vulnerabilities: The Role of Conjugate Variables in System Attacks
Jun-Jie Zhang
Deyu Meng
AAML
60
3
0
16 Feb 2024
TinyLlama: An Open-Source Small Language Model
TinyLlama: An Open-Source Small Language Model
Peiyuan Zhang
Guangtao Zeng
Tianduo Wang
Wei Lu
ALM
LRM
126
390
0
04 Jan 2024
A Universal Law of Robustness via Isoperimetry
A Universal Law of Robustness via Isoperimetry
Sébastien Bubeck
Mark Sellke
38
218
0
26 May 2021
A Survey On Universal Adversarial Attack
A Survey On Universal Adversarial Attack
Chaoning Zhang
Philipp Benz
Chenguo Lin
Adil Karjauv
Jing Wu
In So Kweon
AAML
50
91
0
02 Mar 2021
Globally-Robust Neural Networks
Globally-Robust Neural Networks
Klas Leino
Zifan Wang
Matt Fredrikson
AAML
OOD
110
130
0
16 Feb 2021
Can stable and accurate neural networks be computed? -- On the barriers
  of deep learning and Smale's 18th problem
Can stable and accurate neural networks be computed? -- On the barriers of deep learning and Smale's 18th problem
Matthew J. Colbrook
Vegard Antun
A. Hansen
109
135
0
20 Jan 2021
Robustness May Be at Odds with Fairness: An Empirical Study on
  Class-wise Accuracy
Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy
Philipp Benz
Chaoning Zhang
Adil Karjauv
In So Kweon
AAML
59
59
0
26 Oct 2020
Adversarial Concurrent Training: Optimizing Robustness and Accuracy
  Trade-off of Deep Neural Networks
Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks
Elahe Arani
F. Sarfraz
Bahram Zonooz
AAML
33
9
0
16 Aug 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
743
41,932
0
28 May 2020
Square Attack: a query-efficient black-box adversarial attack via random
  search
Square Attack: a query-efficient black-box adversarial attack via random search
Maksym Andriushchenko
Francesco Croce
Nicolas Flammarion
Matthias Hein
AAML
81
987
0
29 Nov 2019
PIQA: Reasoning about Physical Commonsense in Natural Language
PIQA: Reasoning about Physical Commonsense in Natural Language
Yonatan Bisk
Rowan Zellers
Ronan Le Bras
Jianfeng Gao
Yejin Choi
OOD
LRM
136
1,792
0
26 Nov 2019
High Frequency Component Helps Explain the Generalization of
  Convolutional Neural Networks
High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
Haohan Wang
Xindi Wu
Pengcheng Yin
Eric Xing
59
523
0
28 May 2019
HellaSwag: Can a Machine Really Finish Your Sentence?
HellaSwag: Can a Machine Really Finish Your Sentence?
Rowan Zellers
Ari Holtzman
Yonatan Bisk
Ali Farhadi
Yejin Choi
168
2,468
0
19 May 2019
On instabilities of deep learning in image reconstruction - Does AI come
  at a cost?
On instabilities of deep learning in image reconstruction - Does AI come at a cost?
Vegard Antun
F. Renna
C. Poon
Ben Adcock
A. Hansen
48
603
0
14 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
129
2,549
0
24 Jan 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural
  Networks
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks
Zhi-Qin John Xu
Yaoyu Zhang
Yaoyu Zhang
Yan Xiao
Zheng Ma
121
514
0
19 Jan 2019
SparseFool: a few pixels make a big difference
SparseFool: a few pixels make a big difference
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
53
199
0
06 Nov 2018
Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book
  Question Answering
Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
Todor Mihaylov
Peter Clark
Tushar Khot
Ashish Sabharwal
110
1,528
0
08 Sep 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the
  Robustness of 18 Deep Image Classification Models
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
D. Su
Huan Zhang
Hongge Chen
Jinfeng Yi
Pin-Yu Chen
Yupeng Gao
VLM
112
391
0
05 Aug 2018
Training behavior of deep neural network in frequency domain
Training behavior of deep neural network in frequency domain
Zhi-Qin John Xu
Yaoyu Zhang
Yan Xiao
AI4CE
69
319
0
03 Jul 2018
Robustness May Be at Odds with Accuracy
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
99
1,778
0
30 May 2018
On the importance of single directions for generalization
On the importance of single directions for generalization
Ari S. Morcos
David Barrett
Neil C. Rabinowitz
M. Botvinick
64
333
0
19 Mar 2018
Think you have Solved Question Answering? Try ARC, the AI2 Reasoning
  Challenge
Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Peter Clark
Isaac Cowhey
Oren Etzioni
Tushar Khot
Ashish Sabharwal
Carissa Schoenick
Oyvind Tafjord
ELM
RALM
LRM
158
2,587
0
14 Mar 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Nicholas Carlini
D. Wagner
AAML
94
1,079
0
05 Jan 2018
One pixel attack for fooling deep neural networks
One pixel attack for fooling deep neural networks
Jiawei Su
Danilo Vasconcellos Vargas
Kouichi Sakurai
AAML
117
2,325
0
24 Oct 2017
Adversarial Examples for Evaluating Reading Comprehension Systems
Adversarial Examples for Evaluating Reading Comprehension Systems
Robin Jia
Percy Liang
AAML
ELM
196
1,605
0
23 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
304
12,063
0
19 Jun 2017
Image-to-Image Translation with Conditional Adversarial Networks
Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola
Jun-Yan Zhu
Tinghui Zhou
Alexei A. Efros
SSeg
323
19,643
0
21 Nov 2016
Are Accuracy and Robustness Correlated?
Are Accuracy and Robustness Correlated?
Andras Rozsa
Manuel Günther
Terrance E. Boult
AAML
43
61
0
14 Oct 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
540
5,897
0
08 Jul 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
97
4,167
0
25 Apr 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
193,878
0
10 Dec 2015
The Limitations of Deep Learning in Adversarial Settings
The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot
Patrick McDaniel
S. Jha
Matt Fredrikson
Z. Berkay Celik
A. Swami
AAML
102
3,960
0
24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
148
4,895
0
14 Nov 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
274
19,049
0
20 Dec 2014
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
457
43,649
0
17 Sep 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
268
14,918
1
21 Dec 2013
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