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1412.1897
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Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Computer Vision and Pattern Recognition (CVPR), 2014
5 December 2014
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
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Papers citing
"Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images"
50 / 1,455 papers shown
A Symbolic Neural Network Representation and its Application to Understanding, Verifying, and Patching Networks
Matthew Sotoudeh
Aditya V. Thakur
115
4
0
17 Aug 2019
Computing Linear Restrictions of Neural Networks
Neural Information Processing Systems (NeurIPS), 2019
Matthew Sotoudeh
Aditya V. Thakur
132
24
0
17 Aug 2019
Deep Sparse Band Selection for Hyperspectral Face Recognition
Fariborz Taherkhani
J. Dawson
Nasser M. Nasrabadi
CVBM
141
11
0
15 Aug 2019
Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once
IEEE International Conference on Computer Vision (ICCV), 2019
Jiangfan Han
Xiaoyi Dong
Ruimao Zhang
Dongdong Chen
Weiming Zhang
Nenghai Yu
Ping Luo
Xiaogang Wang
AAML
198
31
0
14 Aug 2019
PCGAN-CHAR: Progressively Trained Classifier Generative Adversarial Networks for Classification of Noisy Handwritten Bangla Characters
International Conference on Asian Digital Libraries (ICADL), 2019
Qun Liu
Edward Collier
S. Mukhopadhyay
107
10
0
11 Aug 2019
Deep Learning for Detecting Building Defects Using Convolutional Neural Networks
Italian National Conference on Sensors (INS), 2019
H. Perez
J. Tah
Amir H. Mosavi
109
225
0
06 Aug 2019
Not All Adversarial Examples Require a Complex Defense: Identifying Over-optimized Adversarial Examples with IQR-based Logit Thresholding
IEEE International Joint Conference on Neural Network (IJCNN), 2019
Utku Ozbulak
Arnout Van Messem
W. D. Neve
AAML
80
1
0
30 Jul 2019
Towards Adversarially Robust Object Detection
IEEE International Conference on Computer Vision (ICCV), 2019
Haichao Zhang
Jianyu Wang
AAML
ObjD
224
149
0
24 Jul 2019
ImageNet-trained deep neural network exhibits illusion-like response to the Scintillating Grid
Eric Sun
Ron Dekel
160
5
0
21 Jul 2019
ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks
Formal Methods in Computer-Aided Design (FMCAD), 2019
Xuankang Lin
He Zhu
R. Samanta
Suresh Jagannathan
AAML
220
31
0
17 Jul 2019
Natural Adversarial Examples
Computer Vision and Pattern Recognition (CVPR), 2019
Dan Hendrycks
Kevin Zhao
Steven Basart
Jacob Steinhardt
Basel Alomair
OODD
945
1,748
0
16 Jul 2019
Modeling User Selection in Quality Diversity
Annual Conference on Genetic and Evolutionary Computation (GECCO), 2019
Alexander Hagg
A. Asteroth
Thomas Bäck
111
10
0
16 Jul 2019
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning
Fan Yang
Mengnan Du
Helen Zhou
XAI
ELM
202
77
0
16 Jul 2019
A Systematic Mapping Study on Testing of Machine Learning Programs
S. Sherin
Muhammad Uzair Khan
Muhammad Zohaib Z. Iqbal
96
13
0
11 Jul 2019
Prior Activation Distribution (PAD): A Versatile Representation to Utilize DNN Hidden Units
L. Meegahapola
Vengateswaran Subramaniam
Lance M. Kaplan
Archan Misra
120
3
0
05 Jul 2019
Treant: Training Evasion-Aware Decision Trees
Data mining and knowledge discovery (DMKD), 2019
Stefano Calzavara
Claudio Lucchese
Gabriele Tolomei
S. Abebe
S. Orlando
AAML
142
43
0
02 Jul 2019
Evolving Robust Neural Architectures to Defend from Adversarial Attacks
Shashank Kotyan
Danilo Vasconcellos Vargas
OOD
AAML
150
37
0
27 Jun 2019
Evolutionary Computation and AI Safety: Research Problems Impeding Routine and Safe Real-world Application of Evolution
Genetic Programming Theory and Practice (GPTP), 2019
Joel Lehman
136
7
0
24 Jun 2019
Defending Against Adversarial Examples with K-Nearest Neighbor
Chawin Sitawarin
David Wagner
AAML
191
29
0
23 Jun 2019
Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications
David Ruhe
Giovanni Cina
Michele Tonutti
D. D. Bruin
Paul Elbers
OOD
106
14
0
20 Jun 2019
Representation Quality Of Neural Networks Links To Adversarial Attacks and Defences
Shashank Kotyan
Danilo Vasconcellos Vargas
Moe Matsuki
263
0
0
15 Jun 2019
Adversarial Robustness Assessment: Why both
L
0
L_0
L
0
and
L
∞
L_\infty
L
∞
Attacks Are Necessary
Shashank Kotyan
Danilo Vasconcellos Vargas
AAML
168
8
0
14 Jun 2019
Evolutionary Trigger Set Generation for DNN Black-Box Watermarking
Jiabao Guo
M. Potkonjak
AAML
WIGM
166
18
0
11 Jun 2019
Proposed Guidelines for the Responsible Use of Explainable Machine Learning
Patrick Hall
Navdeep Gill
N. Schmidt
SILM
XAI
FaML
215
29
0
08 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks
Neural Information Processing Systems (NeurIPS), 2019
Maksym Andriushchenko
Matthias Hein
217
66
0
08 Jun 2019
Outlier Exposure with Confidence Control for Out-of-Distribution Detection
Aristotelis-Angelos Papadopoulos
Mohammad Reza Rajati
Nazim Shaikh
Jiamian Wang
OODD
113
1
0
08 Jun 2019
Defending Against Universal Attacks Through Selective Feature Regeneration
Tejas S. Borkar
Felix Heide
Lina Karam
AAML
222
1
0
08 Jun 2019
Likelihood Ratios for Out-of-Distribution Detection
Neural Information Processing Systems (NeurIPS), 2019
Jie Jessie Ren
Peter J. Liu
Emily Fertig
Jasper Snoek
Ryan Poplin
M. DePristo
Joshua V. Dillon
Balaji Lakshminarayanan
OODD
547
786
0
07 Jun 2019
Robust Attacks against Multiple Classifiers
Juan C. Perdomo
Yaron Singer
AAML
144
11
0
06 Jun 2019
What do AI algorithms actually learn? - On false structures in deep learning
L. Thesing
Vegard Antun
A. Hansen
106
21
0
04 Jun 2019
Improving Variational Autoencoder with Deep Feature Consistent and Generative Adversarial Training
Xianxu Hou
Ke Sun
Linlin Shen
Guoping Qiu
GAN
DRL
162
56
0
04 Jun 2019
A Case for Backward Compatibility for Human-AI Teams
Gagan Bansal
Besmira Nushi
Ece Kamar
Daniel S. Weld
Walter S. Lasecki
Eric Horvitz
300
9
0
04 Jun 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward
IEEE Communications Surveys and Tutorials (COMST), 2019
A. Qayyum
Muhammad Usama
Junaid Qadir
Ala I. Al-Fuqaha
AAML
220
211
0
29 May 2019
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade
Journal of Mathematical Imaging and Vision (JMIV), 2019
T. Lindeberg
282
21
0
29 May 2019
Cross-Domain Transferability of Adversarial Perturbations
Neural Information Processing Systems (NeurIPS), 2019
Muzammal Naseer
Salman H. Khan
M. H. Khan
Fahad Shahbaz Khan
Fatih Porikli
AAML
490
171
0
28 May 2019
GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification
International Conference on Learning Representations (ICLR), 2019
Xuwang Yin
Soheil Kolouri
Gustavo K. Rohde
AAML
240
47
0
27 May 2019
AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence
Jeff Clune
375
131
0
27 May 2019
Combating Label Noise in Deep Learning Using Abstention
International Conference on Machine Learning (ICML), 2019
S. Thulasidasan
Tanmoy Bhattacharya
J. Bilmes
Gopinath Chennupati
J. Mohd-Yusof
NoLa
196
194
0
27 May 2019
Adversarial Distillation for Ordered Top-k Attacks
Zekun Zhang
Tianfu Wu
AAML
126
2
0
25 May 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data
Neural Information Processing Systems (NeurIPS), 2019
Amir Najafi
S. Maeda
Masanori Koyama
Takeru Miyato
OOD
207
135
0
24 May 2019
Convergence and Margin of Adversarial Training on Separable Data
Zachary B. Charles
Shashank Rajput
S. Wright
Dimitris Papailiopoulos
AAML
137
17
0
22 May 2019
Detecting Adversarial Examples and Other Misclassifications in Neural Networks by Introspection
Jonathan Aigrain
Marcin Detyniecki
AAML
158
30
0
22 May 2019
A framework for the extraction of Deep Neural Networks by leveraging public data
Soham Pal
Yash Gupta
Aditya Shukla
Aditya Kanade
S. Shevade
V. Ganapathy
FedML
MLAU
MIACV
159
61
0
22 May 2019
CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models
Sanjay Kariyappa
Jette Henderson
Joydeep Ghosh
198
98
0
20 May 2019
Testing DNN Image Classifiers for Confusion & Bias Errors
International Conference on Software Engineering (ICSE), 2019
Yuchi Tian
Ziyuan Zhong
Vicente Ordonez
Gail E. Kaiser
Baishakhi Ray
306
54
0
20 May 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain
IEEE Transactions on Dependable and Secure Computing (TDSC), 2019
Lei Bu
Yuchao Duan
Fu Song
Zhe Zhao
AAML
377
23
0
19 May 2019
ROSA: Robust Salient Object Detection against Adversarial Attacks
IEEE Transactions on Cybernetics (IEEE Trans. Cybern.), 2019
Haofeng Li
Guanbin Li
Yizhou Yu
AAML
176
31
0
09 May 2019
Learning with Learned Loss Function: Speech Enhancement with Quality-Net to Improve Perceptual Evaluation of Speech Quality
IEEE Signal Processing Letters (SPL), 2019
Szu-Wei Fu
Chien-Feng Liao
Yu Tsao
201
72
0
06 May 2019
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples
Vikash Sehwag
A. Bhagoji
Liwei Song
Chawin Sitawarin
Daniel Cullina
M. Chiang
Prateek Mittal
OODD
213
26
0
05 May 2019
Analysis of Confident-Classifiers for Out-of-distribution Detection
Sachin Vernekar
Ashish Gaurav
Taylor Denouden
Buu Phan
Vahdat Abdelzad
Rick Salay
Krzysztof Czarnecki
OODD
195
18
0
27 Apr 2019
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