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Title
Targeted perturbations reveal brain-like local coding axes in robustified, but not standard, ANN-based brain models Nikolas McNeal N. Apurva Ratan Murty AAML 88 0 0 27 Sep 2025
Limited but consistent gains in adversarial robustness by co-training object recognition models with human EEG Manshan Guo Bhavin Choksi Sari Saba-Sadiya A. T. Gifford Martina G. Vilas Radoslaw Martin Cichy Gemma Roig AAML 155 1 0 05 Sep 2024
Statistical Challenges with Dataset Construction: Why You Will Never Have Enough Images Josh Goldman John K. Tsotsos 131 2 0 20 Aug 2024
PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition Xiao-Li Li Yining Liu Na Dong Sitian Qin Xiaolin Hu 251 7 0 15 Jul 2024
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learningCognitive Systems Research (Cogn. Syst. Res.), 2023 F. Mumuni A. Mumuni AAML 262 16 0 11 Mar 2024
Comparing supervised learning dynamics: Deep neural networks match human data efficiency but show a generalisation lag Lukas Huber Fred W. Mast Felix A. Wichmann 245 1 0 14 Feb 2024
Neither hype nor gloom do DNNs justiceBehavioral and Brain Sciences (BBS), 2022 Gaurav Malhotra Christian Tsvetkov B. D. Evans 295 157 0 08 Dec 2023
Intrinsic Biologically Plausible Adversarial Robustness Matilde Tristany Farinha Thomas Ortner Giorgia Dellaferrera Benjamin Grewe A. Pantazi AAML 375 0 0 29 Sep 2023
Spatial-frequency channels, shape bias, and adversarial robustnessNeural Information Processing Systems (NeurIPS), 2023 Ajay Subramanian E. Sizikova N. Majaj D. Pelli AAML 148 26 0 22 Sep 2023
Robustified ANNs Reveal Wormholes Between Human Category Percepts Guy Gaziv Michael J. Lee J. DiCarlo AAML 121 9 0 14 Aug 2023
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception Drew Linsley Pinyuan Feng Thibaut Boissin A. Ashok Thomas Fel Stephanie Olaiya Thomas Serre AAML 201 9 0 05 Jun 2023
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?Annual Review of Vision Science (ARVS), 2023 Felix Wichmann Robert Geirhos 208 37 0 26 May 2023
Noise robust neural network architecture Yunuo Xiong Hongwei Xiong 120 1 0 16 May 2023
The Representational Status of Deep Learning Models Eamon Duede 264 3 0 21 Mar 2023
Language-Driven Anchors for Zero-Shot Adversarial RobustnessComputer Vision and Pattern Recognition (CVPR), 2023 Xiao-Li Li Wei Emma Zhang Yining Liu Zhan Hu Bo Zhang Xiaolin Hu 224 19 0 30 Jan 2023
Recognizing Object by Components with Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Xiao-Li Li Ziqi Wang Bo Zhang Gang Hua Xiaolin Hu 189 32 0 04 Dec 2022
Extreme Image Transformations Affect Humans and Machines DifferentlyBiological cybernetics (Biol Cybern), 2022 Girik Malik Dakarai Crowder E. Mingolla AAML 230 3 0 30 Nov 2022
Is current research on adversarial robustness addressing the right problem? Ali Borji OOD AAML 119 1 0 31 Jul 2022
Adversarially trained neural representations may already be as robust as corresponding biological neural representations Chong Guo Michael J. Lee Guillaume Leclerc Joel Dapello Yug Rao Aleksander Madry J. DiCarlo GAN AAML 93 16 0 19 Jun 2022
Robustness of Humans and Machines on Object Recognition with Extreme Image Transformations Dakarai Crowder Girik Malik OOD AAML 171 4 0 09 May 2022
Designing Perceptual Puzzles by Differentiating Probabilistic ProgramsInternational Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 2022 Kartik Chandra Tzu-Mao Li J. Tenenbaum Jonathan Ragan-Kelley AAML 97 23 0 26 Apr 2022
Image classifiers can not be made robust to small perturbations Zheng Dai David K Gifford VLM AAML 159 1 0 07 Dec 2021
Human Imperceptible Attacks and Applications to Improve Fairness Xinru Hua Huanzhong Xu Jose H. Blanchet V. Nguyen AAML 159 4 0 30 Nov 2021
Why Out-of-distribution Detection in CNNs Does Not Like Mahalanobis -- and What to Use Instead Kamil Szyc T. Walkowiak H. Maciejewski OODD 84 0 0 13 Oct 2021
The Effects of Image Distribution and Task on Adversarial Robustness Owen Kunhardt Arturo Deza T. Poggio 130 3 0 21 Feb 2021
Evaluating adversarial robustness in simulated cerebellum Liu Yuezhang Bo Li Qifeng Chen AAML 213 2 0 05 Dec 2020
Human vs. supervised machine learning: Who learns patterns faster?Cognitive Systems Research (Cogn. Syst. Res.), 2020 Niklas Kühl Marc Goutier Lucas Baier C. Wolff Dominik Martin 257 49 0 30 Nov 2020
Fooling the primate brain with minimal, targeted image manipulation Li-xin Yuan Will Xiao Giorgia Dellaferrera Gabriel Kreiman Francis E. H. Tay Jiashi Feng Margaret Livingstone AAML 272 1 0 11 Nov 2020
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation LearningNeural Information Processing Systems (NeurIPS), 2020 Iro Laina Ruth C. Fong Andrea Vedaldi OCL 146 13 0 27 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial RobustnessProceedings of the IEEE (Proc. IEEE), 2020 Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 328 50 0 19 Oct 2020
Relationship between manifold smoothness and adversarial vulnerability in deep learning with local errors Zijian Jiang Jianwen Zhou Haiping Huang AAML 108 9 0 04 Jul 2020
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks Xiang Zhang Marinka Zitnik AAML 358 346 0 15 Jun 2020
Five Points to Check when Comparing Visual Perception in Humans and Machines Christina M. Funke Judy Borowski Karolina Stosio Wieland Brendel Thomas S. A. Wallis Matthias Bethge 148 34 0 20 Apr 2020
$Can you hear me $\textit{now}$? Sensitive comparisons of human and machine perception$ Can you hear me $\textit{now}$ ? Sensitive comparisons of human and machine perceptionCognitive Sciences (CogSci), 2020 Michael A. Lepori C. Firestone AAML 188 10 0 27 Mar 2020
Adversarial Examples and the Deeper Riddle of Induction: The Need for a Theory of Artifacts in Deep Learning Cameron Buckner AAML 46 3 0 20 Mar 2020
A Hierarchy of Limitations in Machine Learning M. Malik 159 66 0 12 Feb 2020
Controversial stimuli: pitting neural networks against each other as models of human recognition Tal Golan Prashant C. Raju N. Kriegeskorte AAML 199 39 0 21 Nov 2019
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks Katherine L. Hermann Ting Chen Simon Kornblith CVBM 301 21 0 20 Nov 2019
Universal Physical Camouflage Attacks on Object DetectorsComputer Vision and Pattern Recognition (CVPR), 2019 Lifeng Huang Chengying Gao Yuyin Zhou Cihang Xie Alan Yuille C. Zou Ning Liu AAML 247 197 0 10 Sep 2019
Playing magic tricks to deep neural networks untangles human deception Regina Zaghi-Lara Miguel A. Gea J. Camí Luis M. Martínez A. Gomez-Marin 93 7 0 20 Aug 2019
Human detection of machine manipulated mediaCommunications of the ACM (CACM), 2019 Matthew Groh Ziv Epstein Nick Obradovich Manuel Cebrian Iyad Rahwan 127 22 0 06 Jul 2019
Improving the robustness of ImageNet classifiers using elements of human visual cognitionInternational Conference on Learning Representations (ICLR), 2019 A. Orhan Brenden M. Lake VLM 131 5 0 20 Jun 2019
A Surprising Density of Illusionable Natural SpeechAnnual Meeting of the Cognitive Science Society (CogSci), 2019 M. Guan Gregory Valiant AAML 146 3 0 03 Jun 2019
Rearchitecting Classification Frameworks For Increased Robustness Varun Chandrasekaran Brian Tang Nicolas Papernot Kassem Fawaz S. Jha Xi Wu AAML OOD 247 8 0 26 May 2019
Deep Nets: What have they ever done for Vision? Alan Yuille Chenxi Liu 412 106 0 10 May 2018

Title

Targeted perturbations reveal brain-like local coding axes in robustified, but not standard, ANN-based brain models

Nikolas McNeal

N. Apurva Ratan Murty

AAML

27 Sep 2025

Limited but consistent gains in adversarial robustness by co-training object recognition models with human EEG

Radoslaw Martin Cichy

Gemma Roig

AAML

155

05 Sep 2024

Statistical Challenges with Dataset Construction: Why You Will Never Have Enough Images

Josh Goldman

John K. Tsotsos

131

20 Aug 2024

PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition

251

15 Jul 2024

Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learningCognitive Systems Research (Cogn. Syst. Res.), 2023

F. Mumuni

A. Mumuni

AAML

262

11 Mar 2024

Comparing supervised learning dynamics: Deep neural networks match human data efficiency but show a generalisation lag

Lukas Huber

Fred W. Mast

Felix A. Wichmann

245

14 Feb 2024

Neither hype nor gloom do DNNs justiceBehavioral and Brain Sciences (BBS), 2022

Gaurav Malhotra

Christian Tsvetkov

B. D. Evans

295

157

08 Dec 2023

Intrinsic Biologically Plausible Adversarial Robustness

Matilde Tristany Farinha

375

29 Sep 2023

Spatial-frequency channels, shape bias, and adversarial robustnessNeural Information Processing Systems (NeurIPS), 2023

148

22 Sep 2023

Robustified ANNs Reveal Wormholes Between Human Category Percepts

121

14 Aug 2023

Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception

201

05 Jun 2023

Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?Annual Review of Vision Science (ARVS), 2023

Felix Wichmann

Robert Geirhos

208

26 May 2023

Noise robust neural network architecture

Yunuo Xiong

Hongwei Xiong

120

16 May 2023

The Representational Status of Deep Learning Models

Eamon Duede

264

21 Mar 2023

Language-Driven Anchors for Zero-Shot Adversarial RobustnessComputer Vision and Pattern Recognition (CVPR), 2023

224

30 Jan 2023

Recognizing Object by Components with Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022

189

04 Dec 2022

Extreme Image Transformations Affect Humans and Machines DifferentlyBiological cybernetics (Biol Cybern), 2022

230

30 Nov 2022

Is current research on adversarial robustness addressing the right problem?

Ali Borji

OOD AAML

119

31 Jul 2022

Adversarially trained neural representations may already be as robust as corresponding biological neural representations

19 Jun 2022

Robustness of Humans and Machines on Object Recognition with Extreme Image Transformations

Dakarai Crowder

Girik Malik

OOD AAML

171

09 May 2022

Designing Perceptual Puzzles by Differentiating Probabilistic ProgramsInternational Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 2022

Kartik Chandra

Tzu-Mao Li

J. Tenenbaum

Jonathan Ragan-Kelley

AAML

26 Apr 2022

Image classifiers can not be made robust to small perturbations

Zheng Dai

David K Gifford

VLM AAML

159

07 Dec 2021

Human Imperceptible Attacks and Applications to Improve Fairness

159

30 Nov 2021

Why Out-of-distribution Detection in CNNs Does Not Like Mahalanobis -- and What to Use Instead

13 Oct 2021

The Effects of Image Distribution and Task on Adversarial Robustness

Owen Kunhardt

Arturo Deza

T. Poggio

130

21 Feb 2021

Evaluating adversarial robustness in simulated cerebellum

213

05 Dec 2020

Human vs. supervised machine learning: Who learns patterns faster?Cognitive Systems Research (Cogn. Syst. Res.), 2020

Niklas Kühl

257

30 Nov 2020

Fooling the primate brain with minimal, targeted image manipulation

272

11 Nov 2020

Quantifying Learnability and Describability of Visual Concepts Emerging in Representation LearningNeural Information Processing Systems (NeurIPS), 2020

Iro Laina

Ruth C. Fong

Andrea Vedaldi

OCL

146

27 Oct 2020

Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial RobustnessProceedings of the IEEE (Proc. IEEE), 2020

Guillermo Ortiz-Jiménez

Apostolos Modas

Seyed-Mohsen Moosavi-Dezfooli

P. Frossard

AAML

328

19 Oct 2020

Relationship between manifold smoothness and adversarial vulnerability in deep learning with local errors

108

04 Jul 2020

GNNGuard: Defending Graph Neural Networks against Adversarial Attacks

Xiang Zhang

Marinka Zitnik

AAML

358

346

15 Jun 2020

Five Points to Check when Comparing Visual Perception in Humans and Machines

Wieland Brendel

148

20 Apr 2020

$Can you hear me $\textit{now}$? Sensitive comparisons of human and machine perception$

Can you hear me

\textit{now}

? Sensitive comparisons of human and machine perceptionCognitive Sciences (CogSci), 2020

Michael A. Lepori

C. Firestone

AAML

188

27 Mar 2020

Adversarial Examples and the Deeper Riddle of Induction: The Need for a Theory of Artifacts in Deep Learning

Cameron Buckner

AAML

20 Mar 2020

A Hierarchy of Limitations in Machine Learning

M. Malik

159

12 Feb 2020

Controversial stimuli: pitting neural networks against each other as models of human recognition

199

21 Nov 2019

The Origins and Prevalence of Texture Bias in Convolutional Neural Networks

301

20 Nov 2019

Universal Physical Camouflage Attacks on Object DetectorsComputer Vision and Pattern Recognition (CVPR), 2019

Cihang Xie

247

197

10 Sep 2019

Playing magic tricks to deep neural networks untangles human deception

20 Aug 2019

Human detection of machine manipulated mediaCommunications of the ACM (CACM), 2019

127

06 Jul 2019

Improving the robustness of ImageNet classifiers using elements of human visual cognitionInternational Conference on Learning Representations (ICLR), 2019

A. Orhan

Brenden M. Lake

VLM

131

20 Jun 2019

A Surprising Density of Illusionable Natural SpeechAnnual Meeting of the Cognitive Science Society (CogSci), 2019

M. Guan

Gregory Valiant

AAML

146

03 Jun 2019

Rearchitecting Classification Frameworks For Increased Robustness

247

26 May 2019

Deep Nets: What have they ever done for Vision?

Alan Yuille

Chenxi Liu

412

106

10 May 2018

Title
Targeted perturbations reveal brain-like local coding axes in robustified, but not standard, ANN-based brain models Nikolas McNeal N. Apurva Ratan Murty AAML 88 0 0 27 Sep 2025
Limited but consistent gains in adversarial robustness by co-training object recognition models with human EEG Manshan Guo Bhavin Choksi Sari Saba-Sadiya A. T. Gifford Martina G. Vilas Radoslaw Martin Cichy Gemma Roig AAML 155 1 0 05 Sep 2024
Statistical Challenges with Dataset Construction: Why You Will Never Have Enough Images Josh Goldman John K. Tsotsos 131 2 0 20 Aug 2024
PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition Xiao-Li Li Yining Liu Na Dong Sitian Qin Xiaolin Hu 251 7 0 15 Jul 2024
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learningCognitive Systems Research (Cogn. Syst. Res.), 2023 F. Mumuni A. Mumuni AAML 262 16 0 11 Mar 2024
Comparing supervised learning dynamics: Deep neural networks match human data efficiency but show a generalisation lag Lukas Huber Fred W. Mast Felix A. Wichmann 245 1 0 14 Feb 2024
Neither hype nor gloom do DNNs justiceBehavioral and Brain Sciences (BBS), 2022 Gaurav Malhotra Christian Tsvetkov B. D. Evans 295 157 0 08 Dec 2023
Intrinsic Biologically Plausible Adversarial Robustness Matilde Tristany Farinha Thomas Ortner Giorgia Dellaferrera Benjamin Grewe A. Pantazi AAML 375 0 0 29 Sep 2023
Spatial-frequency channels, shape bias, and adversarial robustnessNeural Information Processing Systems (NeurIPS), 2023 Ajay Subramanian E. Sizikova N. Majaj D. Pelli AAML 148 26 0 22 Sep 2023
Robustified ANNs Reveal Wormholes Between Human Category Percepts Guy Gaziv Michael J. Lee J. DiCarlo AAML 121 9 0 14 Aug 2023
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception Drew Linsley Pinyuan Feng Thibaut Boissin A. Ashok Thomas Fel Stephanie Olaiya Thomas Serre AAML 201 9 0 05 Jun 2023
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?Annual Review of Vision Science (ARVS), 2023 Felix Wichmann Robert Geirhos 208 37 0 26 May 2023
Noise robust neural network architecture Yunuo Xiong Hongwei Xiong 120 1 0 16 May 2023
The Representational Status of Deep Learning Models Eamon Duede 264 3 0 21 Mar 2023
Language-Driven Anchors for Zero-Shot Adversarial RobustnessComputer Vision and Pattern Recognition (CVPR), 2023 Xiao-Li Li Wei Emma Zhang Yining Liu Zhan Hu Bo Zhang Xiaolin Hu 224 19 0 30 Jan 2023
Recognizing Object by Components with Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Xiao-Li Li Ziqi Wang Bo Zhang Gang Hua Xiaolin Hu 189 32 0 04 Dec 2022
Extreme Image Transformations Affect Humans and Machines DifferentlyBiological cybernetics (Biol Cybern), 2022 Girik Malik Dakarai Crowder E. Mingolla AAML 230 3 0 30 Nov 2022
Is current research on adversarial robustness addressing the right problem? Ali Borji OOD AAML 119 1 0 31 Jul 2022
Adversarially trained neural representations may already be as robust as corresponding biological neural representations Chong Guo Michael J. Lee Guillaume Leclerc Joel Dapello Yug Rao Aleksander Madry J. DiCarlo GAN AAML 93 16 0 19 Jun 2022
Robustness of Humans and Machines on Object Recognition with Extreme Image Transformations Dakarai Crowder Girik Malik OOD AAML 171 4 0 09 May 2022
Designing Perceptual Puzzles by Differentiating Probabilistic ProgramsInternational Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 2022 Kartik Chandra Tzu-Mao Li J. Tenenbaum Jonathan Ragan-Kelley AAML 97 23 0 26 Apr 2022
Image classifiers can not be made robust to small perturbations Zheng Dai David K Gifford VLM AAML 159 1 0 07 Dec 2021
Human Imperceptible Attacks and Applications to Improve Fairness Xinru Hua Huanzhong Xu Jose H. Blanchet V. Nguyen AAML 159 4 0 30 Nov 2021
Why Out-of-distribution Detection in CNNs Does Not Like Mahalanobis -- and What to Use Instead Kamil Szyc T. Walkowiak H. Maciejewski OODD 84 0 0 13 Oct 2021
The Effects of Image Distribution and Task on Adversarial Robustness Owen Kunhardt Arturo Deza T. Poggio 130 3 0 21 Feb 2021
Evaluating adversarial robustness in simulated cerebellum Liu Yuezhang Bo Li Qifeng Chen AAML 213 2 0 05 Dec 2020
Human vs. supervised machine learning: Who learns patterns faster?Cognitive Systems Research (Cogn. Syst. Res.), 2020 Niklas Kühl Marc Goutier Lucas Baier C. Wolff Dominik Martin 257 49 0 30 Nov 2020
Fooling the primate brain with minimal, targeted image manipulation Li-xin Yuan Will Xiao Giorgia Dellaferrera Gabriel Kreiman Francis E. H. Tay Jiashi Feng Margaret Livingstone AAML 272 1 0 11 Nov 2020
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation LearningNeural Information Processing Systems (NeurIPS), 2020 Iro Laina Ruth C. Fong Andrea Vedaldi OCL 146 13 0 27 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial RobustnessProceedings of the IEEE (Proc. IEEE), 2020 Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 328 50 0 19 Oct 2020
Relationship between manifold smoothness and adversarial vulnerability in deep learning with local errors Zijian Jiang Jianwen Zhou Haiping Huang AAML 108 9 0 04 Jul 2020
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks Xiang Zhang Marinka Zitnik AAML 358 346 0 15 Jun 2020
Five Points to Check when Comparing Visual Perception in Humans and Machines Christina M. Funke Judy Borowski Karolina Stosio Wieland Brendel Thomas S. A. Wallis Matthias Bethge 148 34 0 20 Apr 2020
$Can you hear me $\textit{now}$? Sensitive comparisons of human and machine perception$ Can you hear me $\textit{now}$ ? Sensitive comparisons of human and machine perceptionCognitive Sciences (CogSci), 2020 Michael A. Lepori C. Firestone AAML 188 10 0 27 Mar 2020
Adversarial Examples and the Deeper Riddle of Induction: The Need for a Theory of Artifacts in Deep Learning Cameron Buckner AAML 46 3 0 20 Mar 2020
A Hierarchy of Limitations in Machine Learning M. Malik 159 66 0 12 Feb 2020
Controversial stimuli: pitting neural networks against each other as models of human recognition Tal Golan Prashant C. Raju N. Kriegeskorte AAML 199 39 0 21 Nov 2019
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks Katherine L. Hermann Ting Chen Simon Kornblith CVBM 301 21 0 20 Nov 2019
Universal Physical Camouflage Attacks on Object DetectorsComputer Vision and Pattern Recognition (CVPR), 2019 Lifeng Huang Chengying Gao Yuyin Zhou Cihang Xie Alan Yuille C. Zou Ning Liu AAML 247 197 0 10 Sep 2019
Playing magic tricks to deep neural networks untangles human deception Regina Zaghi-Lara Miguel A. Gea J. Camí Luis M. Martínez A. Gomez-Marin 93 7 0 20 Aug 2019
Human detection of machine manipulated mediaCommunications of the ACM (CACM), 2019 Matthew Groh Ziv Epstein Nick Obradovich Manuel Cebrian Iyad Rahwan 127 22 0 06 Jul 2019
Improving the robustness of ImageNet classifiers using elements of human visual cognitionInternational Conference on Learning Representations (ICLR), 2019 A. Orhan Brenden M. Lake VLM 131 5 0 20 Jun 2019
A Surprising Density of Illusionable Natural SpeechAnnual Meeting of the Cognitive Science Society (CogSci), 2019 M. Guan Gregory Valiant AAML 146 3 0 03 Jun 2019
Rearchitecting Classification Frameworks For Increased Robustness Varun Chandrasekaran Brian Tang Nicolas Papernot Kassem Fawaz S. Jha Xi Wu AAML OOD 247 8 0 26 May 2019
Deep Nets: What have they ever done for Vision? Alan Yuille Chenxi Liu 412 106 0 10 May 2018

Title

Targeted perturbations reveal brain-like local coding axes in robustified, but not standard, ANN-based brain models

Nikolas McNeal

N. Apurva Ratan Murty

AAML

27 Sep 2025

Limited but consistent gains in adversarial robustness by co-training object recognition models with human EEG