The MusiNet project: Addressing the challenges in Networked Music Performance systems. - Demosthenes Akoumianakis; Chrisoula Alexandraki; V. Alexiou; Christina Anagnostopoulou; A. Eleftheriadis; Vasiliki Lalioti; Yiannis Mastorakis; Apostolos Modas; Athanasios Mouchtaris; Despoina Pavlidi; George C. Polyzos; Panagiotis Tsakalides; et al. (IISA, 2015)

Shared-variable Synchronization Approaches for Dynamic Data Flow Programs. - Apostolos Modas; Simone Casale Brunet; Robert J. Stewart 001; Endri Bezati; Junaid Jameel Ahmad; Marco Mattavelli (SiPS, 2018)

SparseFool: A Few Pixels Make a Big Difference. - Apostolos Modas; Seyed-Mohsen Moosavi-Dezfooli; Pascal Frossard (CVPR, 2019)

Multi-View Shape Estimation of Transparent Containers. - Alessio Xompero; Ricardo Sanchez-Matilla; Apostolos Modas; Pascal Frossard; Andrea Cavallaro (ICASSP, 2020)

Hold me tight! Influence of discriminative features on deep network boundaries. - Guillermo Ortiz-Jiménez; Apostolos Modas; Seyed-Mohsen Moosavi-Dezfooli; Pascal Frossard (NeurIPS, 2020)

Neural Anisotropy Directions. - Guillermo Ortiz-Jiménez; Apostolos Modas; Seyed-Mohsen Moosavi-Dezfooli; Pascal Frossard (NeurIPS, 2020)

Towards robust sensing for Autonomous Vehicles: An adversarial perspective. - Apostolos Modas; Ricardo Sanchez-Matilla; Pascal Frossard; Andrea Cavallaro (CoRR, 2020)

Benchmark for Human-to-Robot Handovers of Unseen Containers With Unknown Filling. - Ricardo Sanchez-Matilla; Konstantinos I. Chatzilygeroudis; Apostolos Modas; Nuno Ferreira Duarte; Alessio Xompero; Pascal Frossard; Aude Billard; Andrea Cavallaro (IEEE Robotics Autom. Lett., 2020)

Toward Robust Sensing for Autonomous Vehicles: An Adversarial Perspective. - Apostolos Modas; Ricardo Sanchez-Matilla; Pascal Frossard; Andrea Cavallaro (IEEE Signal Process. Mag., 2020)

Improving Filling Level Classification with Adversarial Training. - Apostolos Modas; Alessio Xompero; Ricardo Sanchez-Matilla; Pascal Frossard; Andrea Cavallaro (ICIP, 2021)

A neural anisotropic view of underspecification in deep learning. - Guillermo Ortiz-Jiménez; Itamar Franco Salazar-Reque; Apostolos Modas; Seyed-Mohsen Moosavi-Dezfooli; Pascal Frossard (CoRR, 2021)

Optimism in the Face of Adversity: Understanding and Improving Deep Learning Through Adversarial Robustness. - Guillermo Ortiz-Jiménez; Apostolos Modas; Seyed-Mohsen Moosavi-Dezfooli; Pascal Frossard (Proc. IEEE, 2021)

Crop - CORSMAL Containers Manipulation (C-CCM). - Ricardo Sanchez-Matilla; Alessio Xompero; Apostolos Modas; Pascal Frossard; Andrea Cavallaro (Zenodo, 2021)

PRIME: A Few Primitives Can Boost Robustness to Common Corruptions. - Apostolos Modas; Rahul Rade; Guillermo Ortiz-Jiménez; Seyed-Mohsen Moosavi-Dezfooli; Pascal Frossard (ECCV (25), 2022)

Data augmentation with mixtures of max-entropy transformations for filling-level classification. - Apostolos Modas; Andrea Cavallaro; Pascal Frossard (EUSIPCO, 2022)

Robustness and invariance properties of image classifiers. - Apostolos Modas (CoRR, 2022)

Ethical Considerations for Responsible Data Curation. - Jerone Theodore Alexander Andrews; Dora Zhao; William Thong; Apostolos Modas; Orestis Papakyriakopoulos; Alice Xiang (NeurIPS, 2023)

Ethical Considerations for Collecting Human-Centric Image Datasets. - Jerone T. A. Andrews; Dora Zhao; William Thong; Apostolos Modas; Orestis Papakyriakopoulos; Shruti Nagpal; Alice Xiang (CoRR, 2023)

Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes. - Yusuke Hirota; Jerone Theodore Alexander Andrews; Dora Zhao; Orestis Papakyriakopoulos; Apostolos Modas; Yuta Nakashima; Alice Xiang (EMNLP, 2024)