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2308.06612
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On the Interplay of Convolutional Padding and Adversarial Robustness
12 August 2023
Paul Gavrikov
J. Keuper
AAML
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Papers citing
"On the Interplay of Convolutional Padding and Adversarial Robustness"
22 / 22 papers shown
Title
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters
Paul Gavrikov
J. Keuper
AAML
65
31
0
29 Mar 2022
MAT: Mask-Aware Transformer for Large Hole Image Inpainting
Wenbo Li
Zhe Lin
Kun Zhou
Lu Qi
Yi Wang
Jiaya Jia
53
313
0
29 Mar 2022
Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks
Qiyu Kang
Yang Song
Qinxu Ding
Wee Peng Tay
AAML
36
92
0
25 Oct 2021
Spectral Leakage and Rethinking the Kernel Size in CNNs
Nergis Tomen
Jan van Gemert
AAML
34
18
0
25 Jan 2021
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Sven Gowal
Chongli Qin
J. Uesato
Timothy A. Mann
Pushmeet Kohli
AAML
39
328
0
07 Oct 2020
Inverting Gradients -- How easy is it to break privacy in federated learning?
Jonas Geiping
Hartmut Bauermeister
Hannah Dröge
Michael Moeller
FedML
75
1,217
0
31 Mar 2020
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
O. Kayhan
Jan van Gemert
284
234
0
16 Mar 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce
Matthias Hein
AAML
196
1,821
0
03 Mar 2020
Overfitting in adversarially robust deep learning
Leslie Rice
Eric Wong
Zico Kolter
77
796
0
26 Feb 2020
How Much Position Information Do Convolutional Neural Networks Encode?
Md. Amirul Islam
Sen Jia
Neil D. B. Bruce
SSL
237
346
0
22 Jan 2020
Square Attack: a query-efficient black-box adversarial attack via random search
Maksym Andriushchenko
Francesco Croce
Nicolas Flammarion
Matthias Hein
AAML
59
977
0
29 Nov 2019
InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions
Shikhar Vashishth
Soumya Sanyal
Vikram Nitin
Nilesh Agrawal
Partha P. Talukdar
56
341
0
01 Nov 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
Francesco Croce
Matthias Hein
AAML
82
483
0
03 Jul 2019
On Evaluating Adversarial Robustness
Nicholas Carlini
Anish Athalye
Nicolas Papernot
Wieland Brendel
Jonas Rauber
Dimitris Tsipras
Ian Goodfellow
Aleksander Madry
Alexey Kurakin
ELM
AAML
68
899
0
18 Feb 2019
Towards Fast Computation of Certified Robustness for ReLU Networks
Tsui-Wei Weng
Huan Zhang
Hongge Chen
Zhao Song
Cho-Jui Hsieh
Duane S. Boning
Inderjit S. Dhillon
Luca Daniel
AAML
76
689
0
25 Apr 2018
Evasion Attacks against Machine Learning at Test Time
Battista Biggio
Igino Corona
Davide Maiorca
B. Nelson
Nedim Srndic
Pavel Laskov
Giorgio Giacinto
Fabio Roli
AAML
104
2,142
0
21 Aug 2017
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu
Xinyun Chen
Chang-rui Liu
D. Song
AAML
126
1,727
0
08 Nov 2016
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
450
3,124
0
04 Nov 2016
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
231
8,030
0
13 Aug 2016
Learning to Refine Object Segments
Pedro H. O. Pinheiro
Nayeon Lee
R. Collobert
Piotr Dollàr
SSeg
65
855
0
29 Mar 2016
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
1.1K
39,383
0
01 Sep 2014
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
185
14,831
1
21 Dec 2013
1