Seyed-Mohsen Moosavi-Dezfooli

Amirhossein Asgari-Farsangi

Alireza Abdollahpourrostam

CoRR, 2024

2023

Revisiting DeepFool: generalization and improvement.

[BibT_eX]

[DOI]

Mahed Abroshan

CoRR, 2023

Sparse Attacks for Manipulating Explanations in Deep Neural Network Models.

[BibT_eX]

[DOI]

Ahmad Ajalloeian

Michalis Vlachos

Proceedings of the IEEE International Conference on Data Mining, 2023

How to choose your best allies for a transferable attack?

[BibT_eX]

[DOI]

Thibault Maho

Teddy Furon

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

The Enemy of My Enemy is My Friend: Exploring Inverse Adversaries for Improving Adversarial Training.

[BibT_eX]

[DOI]

Junhao Dong

Jianhuang Lai

Xiaohua Xie

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off.

[BibT_eX]

[DOI]

Rahul Rade

Proceedings of the Tenth International Conference on Learning Representations, 2022

PRIME: A Few Primitives Can Boost Robustness to Common Corruptions.

[BibT_eX]

[DOI]

Rahul Rade

Proceedings of the Computer Vision - ECCV 2022, 2022

Vehicle trajectory prediction works, but not everywhere.

[BibT_eX]

[DOI]

Ahmad Rahimi

Mohammad Shaverdikondori

Amir Hossein Shahidzadeh

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

On Smoothed Explanations: Quality and Robustness.

[BibT_eX]

[DOI]

Ahmad Ajalloeian

Michalis Vlachos

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Optimism in the Face of Adversity: Understanding and Improving Deep Learning Through Adversarial Robustness.

[BibT_eX]

[DOI]

Proc. IEEE, 2021

Vehicle trajectory prediction works, but not everywhere.

[BibT_eX]

[DOI]

Ahmad Rahimi

Mohammad Shaverdikondori

Mohammad Shahidzadeh

CoRR, 2021

Are socially-aware trajectory prediction models really socially-aware?

[BibT_eX]

[DOI]

Pedram Khorsandi

Mohammad Saneian

CoRR, 2021

Adversarial training may be a double-edged sword.

[BibT_eX]

[DOI]

Ali Rahmati

Huaiyu Dai

CoRR, 2021

Understanding Catastrophic Overfitting in Adversarial Training.

[BibT_eX]

[DOI]

Peilin Kang

CoRR, 2021

A neural anisotropic view of underspecification in deep learning.

[BibT_eX]

[DOI]

Itamar Franco Salazar-Reque

CoRR, 2021

What can linearized neural networks actually say about generalization?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Uniform Convergence, Adversarial Spheres and a Simple Remedy.

[BibT_eX]

[DOI]

Gregor Bachmann

Thomas Hofmann

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Neural Anisotropy Directions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Hold me tight! Influence of discriminative features on deep network boundaries.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

GeoDA: A Geometric Framework for Black-Box Adversarial Attacks.

[BibT_eX]

[DOI]

Ali Rahmati

Huaiyu Dai

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Geometry of adversarial robustness of deep networks: methods and applications.

[BibT_eX]

[DOI]

PhD thesis, 2019

A Geometry-Inspired Decision-Based Attack.

[BibT_eX]

[DOI]

Yujia Liu

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Universal Adversarial Attacks on Text Classifiers.

[BibT_eX]

[DOI]

Melika Behjati

Mahdieh Soleymani Baghshah

Proceedings of the IEEE International Conference on Acoustics, 2019

Robustness via Curvature Regularization, and Vice Versa.

[BibT_eX]

[DOI]

Jonathan Uesato

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

SparseFool: A Few Pixels Make a Big Difference.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Divide, Denoise, and Defend against Adversarial Attacks.

[BibT_eX]

[DOI]

Ashish Shrivastava

Oncel Tuzel

CoRR, 2018

Robustness of Classifiers to Universal Perturbations: A Geometric Perspective.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Geometric Robustness of Deep Networks: Analysis and Improvement.

[BibT_eX]

[DOI]

Can Kanbak

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Empirical Study of the Topology and Geometry of Deep Networks.

[BibT_eX]

[DOI]

Stefano Soatto

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Adaptive Quantization for Deep Neural Network.

[BibT_eX]

[DOI]

Yiren Zhou

Ngai-Man Cheung

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

The Robustness of Deep Networks: A Geometrical Perspective.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2017

Analysis of universal adversarial perturbations.

[BibT_eX]

[DOI]

CoRR, 2017

Classification regions of deep neural networks.

[BibT_eX]

[DOI]

Stefano Soatto

CoRR, 2017

Universal Adversarial Perturbations.

[BibT_eX]

[DOI]

Omar Fawzi

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Robustness of classifiers: from adversarial to random noise.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Simultaneous Acoustic Localization of Multiple Smartphones with Euclidean Distance Matrices.

[BibT_eX]

[DOI]

Yvonne-Anne Pignolet

Dacfey Dzung

Proceedings of the International Conference on Embedded Wireless Systems and Networks, 2016

DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks.

[BibT_eX]

[DOI]