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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
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155
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150
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235
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193
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111
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Akshay Chaturvedi
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XGNN: Towards Model-Level Explanations of Graph Neural Networks
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278
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Open-Set Recognition with Gaussian Mixture Variational Autoencoders
AAAI Conference on Artificial Intelligence (AAAI), 2020
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154
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Shapley explainability on the data manifold
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422
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Robust Reinforcement Learning with Wasserstein Constraint
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Liang Pang
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52
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79
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105
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28 May 2020
Evaluation of the general applicability of Dragoon for the k-center problem
Online World Conference on Soft Computing in Industrial Applications (WSCIA), 2016
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20
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28 May 2020
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85
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Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization
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131
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Enhancing Intrinsic Adversarial Robustness via Feature Pyramid Decoder
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Guanlin Li
Shuya Ding
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178
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Explainable Deep Learning: A Field Guide for the Uninitiated
Journal of Artificial Intelligence Research (JAIR), 2020
Gabrielle Ras
Ning Xie
Marcel van Gerven
Derek Doran
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446
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30 Apr 2020
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
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Nathan Inkawhich
Kevin J. Liang
Binghui Wang
Matthew J. Inkawhich
Lawrence Carin
Yiran Chen
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227
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29 Apr 2020
Adversarial Machine Learning in Network Intrusion Detection Systems
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P. Maxwell
Nathaniel D. Bastian
GAN
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181
172
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Assessing the Reliability of Visual Explanations of Deep Models with Adversarial Perturbations
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Tiago Pimentel
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96
3
0
22 Apr 2020
Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution
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Sebastian Lapuschkin
Leander Weber
Wojciech Samek
Alexander Binder
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163
42
0
22 Apr 2020
Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision
European Conference on Computer Vision (ECCV), 2020
Damien Teney
Ehsan Abbasnejad
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223
125
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20 Apr 2020
Shortcut Learning in Deep Neural Networks
Nature Machine Intelligence (NMI), 2020
Robert Geirhos
J. Jacobsen
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R. Zemel
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Felix Wichmann
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2,457
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16 Apr 2020
Investigating Efficient Learning and Compositionality in Generative LSTM Networks
International Conference on Artificial Neural Networks (ICANN), 2020
Sarah Fabi
S. Otte
J. G. Wiese
Martin Volker Butz
72
6
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16 Apr 2020
Towards Robust Classification with Image Quality Assessment
Yeli Feng
Yiyu Cai
172
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0
14 Apr 2020
Convolutional neural net face recognition works in non-human-like ways
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Rosyl S. Somai
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101
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Feature Partitioning for Robust Tree Ensembles and their Certification in Adversarial Scenarios
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184
10
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Class Anchor Clustering: a Loss for Distance-based Open Set Recognition
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199
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Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
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Xiaohang Zhan
Bo Dai
Dahua Lin
Chen Change Loy
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436
417
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30 Mar 2020
Architecture Disentanglement for Deep Neural Networks
IEEE International Conference on Computer Vision (ICCV), 2020
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Liujuan Cao
QiXiang Ye
Tong Tong
Shengchuan Zhang
Ke Li
Feiyue Huang
Rongrong Ji
Ling Shao
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191
21
0
30 Mar 2020
Can you hear me
now
\textit{now}
now
? Sensitive comparisons of human and machine perception
Cognitive Sciences (CogSci), 2020
Michael A. Lepori
C. Firestone
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225
10
0
27 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability
European Conference on Computer Vision (ECCV), 2020
Maximilian Augustin
Alexander Meinke
Matthias Hein
OOD
326
108
0
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Overinterpretation reveals image classification model pathologies
Neural Information Processing Systems (NeurIPS), 2020
Brandon Carter
Siddhartha Jain
Jonas W. Mueller
David K Gifford
FAtt
259
55
0
19 Mar 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications
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G. Montavon
Sebastian Lapuschkin
Christopher J. Anders
K. Müller
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399
87
0
17 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
International Conference on Machine Learning (ICML), 2020
Jize Zhang
B. Kailkhura
T. Y. Han
UQCV
337
260
0
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Hierarchical Models: Intrinsic Separability in High Dimensions
Wen-Yan Lin
114
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Minimum-Norm Adversarial Examples on KNN and KNN-Based Models
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146
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C. Yuan
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113
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Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Neural Information Processing Systems (NeurIPS), 2020
Zhisheng Xiao
Qing Yan
Y. Amit
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391
214
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SAM: The Sensitivity of Attribution Methods to Hyperparameters
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Chirag Agarwal
Anh Nguyen
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166
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Image-based OoD-Detector Principles on Graph-based Input Data in Human Action Recognition
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David Münch
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85
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Sarah Adel Bargal
Stan Sclaroff
PICV
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284
149
0
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Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Marius Hobbhahn
Agustinus Kristiadi
Philipp Hennig
BDL
UQCV
440
39
0
02 Mar 2020
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