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Towards Deep Neural Network Architectures Robust to Adversarial Examples

International Conference on Learning Representations (ICLR), 2014

11 December 2014

Papers citing "Towards Deep Neural Network Architectures Robust to Adversarial Examples"

50 / 417 papers shown

A Provable Defense for Deep Residual Networks

M. Mirman

Gagandeep Singh

Martin Vechev

145

29 Mar 2019

Defending against Whitebox Adversarial Attacks via Randomized Discretization

Yuchen Zhang

Abigail Z. Jacobs

AAML

208

25 Mar 2019

Scalable Differential Privacy with Certified Robustness in Adversarial Learning

397

23 Mar 2019

Detecting Overfitting via Adversarial ExamplesNeural Information Processing Systems (NeurIPS), 2019

230

06 Mar 2019

Accelerating Training of Deep Neural Networks with a Standardization Loss

Jasmine Collins

Johannes Ballé

Jonathon Shlens

182

03 Mar 2019

Adversarial Attack and Defense on Point Sets

209

145

28 Feb 2019

Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples

240

06 Feb 2019

Training Artificial Neural Networks by Generalized Likelihood Ratio Method: Exploring Brain-like Learning to Improve Robustness

103

31 Jan 2019

Augmenting Model Robustness with Transformation-Invariant Attacks

Zhe Wang

149

31 Jan 2019

A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance

146

30 Jan 2019

Optimization Problems for Machine Learning: A Survey

417

225

16 Jan 2019

Image Transformation can make Neural Networks more robust against Adversarial Examples

D. D. Thang

Toshihiro Matsui

AAML

104

10 Jan 2019

A Data-driven Adversarial Examples Recognition Framework via Adversarial Feature Genome

207

25 Dec 2018

DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense

Hang Zhou

150

25 Dec 2018

Spartan Networks: Self-Feature-Squeezing Neural Networks for increased robustness in adversarial settings

17 Dec 2018

Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks

Xiang Li

Shihao Ji

AAML

155

17 Dec 2018

Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach

R. Sahay

Rehana Mahfuz

Aly El Gamal

07 Dec 2018

Adversarial Defense of Image Classification Using a Variational Auto-Encoder

Yi-Si Luo

H. Pfister

AAML

155

07 Dec 2018

On Configurable Defense against Adversarial Example Attacks

Yu Li

103

06 Dec 2018

Regularized Ensembles and Transferability in Adversarial Learning

Yifan Chen

Yevgeniy Vorobeychik

AAML

05 Dec 2018

FineFool: Fine Object Contour Attack via Attention

131

01 Dec 2018

Robustness via curvature regularization, and vice versaComputer Vision and Pattern Recognition (CVPR), 2018

Seyed-Mohsen Moosavi-Dezfooli

202

333

23 Nov 2018

Theoretical Analysis of Adversarial Learning: A Minimax Approach

185

13 Nov 2018

MixTrain: Scalable Training of Verifiably Robust Neural Networks

06 Nov 2018

Rademacher Complexity for Adversarially Robust Generalization

422

280

29 Oct 2018

Towards Robust Deep Neural Networks

238

27 Oct 2018

The Faults in Our Pi Stars: Security Issues and Open Challenges in Deep Reinforcement Learning

Vahid Behzadan

Arslan Munir

158

23 Oct 2018

A Training-based Identification Approach to VIN Adversarial Examples

18 Oct 2018

Provable Robustness of ReLU networks via Maximization of Linear Regions

Francesco Croce

Maksym Andriushchenko

Matthias Hein

233

170

17 Oct 2018

Security Matters: A Survey on Adversarial Machine Learning

238

16 Oct 2018

Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis

M. A. Nabian

Hadi Meidani

PINN AI4CE

210

11 Oct 2018

$Response to Comment on "All-optical machine learning using diffractive deep neural networks"$

Response to Comment on "All-optical machine learning using diffractive deep neural networks"

175

10 Oct 2018

The Outer Product Structure of Neural Network Derivatives

Craig Bakker

Michael J. Henry

Nathan Oken Hodas

09 Oct 2018

Adversarial Examples - A Complete Characterisation of the Phenomenon

253

02 Oct 2018

Training Machine Learning Models by Regularizing their Explanations

A. Ross

FaML

121

29 Sep 2018

Fast Geometrically-Perturbed Adversarial FacesIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2018

191

24 Sep 2018

HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples

178

18 Sep 2018

Adversarial Examples: Opportunities and Challenges

Jiliang Zhang

Chen Li

AAML

241

270

13 Sep 2018

Bridging machine learning and cryptography in defence against adversarial attacks

O. Taran

Shideh Rezaeifar

Svyatoslav Voloshynovskiy

AAML

132

05 Sep 2018

Mitigation of Adversarial Attacks through Embedded Feature Selection

16 Aug 2018

Defense Against Adversarial Attacks with Saak Transform

119

06 Aug 2018

EagleEye: Attack-Agnostic Defense against Adversarial Inputs (Technical Report)

135

01 Aug 2018

Motivating the Rules of the Game for Adversarial Example Research

Justin Gilmer

271

238

18 Jul 2018

Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions

Adnan Siraj Rakin

213

18 Jul 2018

Neural Networks Regularization Through Representation Learning

Soufiane Belharbi

OOD SSL

134

13 Jul 2018

Adversarial Examples in Deep Learning: Characterization and Divergence

Mehmet Emre Gursoy

272

29 Jun 2018

A New Angle on L2 Regularization

T. Tanay

Lewis D. Griffin

LLMSV

129

28 Jun 2018

Detection based Defense against Adversarial Examples from the Steganalysis Point of View

264

107

21 Jun 2018

Gradient Adversarial Training of Neural Networks

162

21 Jun 2018

Built-in Vulnerabilities to Imperceptible Adversarial Perturbations

T. Tanay

Jerone T. A. Andrews

Lewis D. Griffin

156

19 Jun 2018