MesoNet: a Compact Facial Video Forgery Detection Network. - Darius Afchar; Vincent Nozick; Junichi Yamagishi; Isao Echizen (WIFS, 2018)

Making Neural Networks Interpretable with Attribution: Application to Implicit Signals Prediction. - Darius Afchar; Romain Hennequin (RecSys, 2020)

Towards Rigorous Interpretations: a Formalisation of Feature Attribution. - Darius Afchar; Vincent Guigue; Romain Hennequin (ICML, 2021)

Learning Unsupervised Hierarchies of Audio Concepts. - Darius Afchar; Romain Hennequin; Vincent Guigue (ISMIR, 2022)

Explainability in Music Recommender Systems. - Darius Afchar; Alessandro B. Melchiorre; Markus Schedl; Romain Hennequin; Elena V. Epure; Manuel Moussallam (AI Mag., 2022)

Of Spiky SVDs and Music Recommendation. - Darius Afchar; Romain Hennequin; Vincent Guigue (RecSys, 2023)

Interpretable Music Recommender Systems. (Systèmes de recommandation musicale interprétables). - Darius Afchar (2023)

Detecting music deepfakes is easy but actually hard. - Darius Afchar; Gabriel Meseguer-Brocal; Romain Hennequin (CoRR, 2024)

Harnessing High-Level Song Descriptors towards Natural Language-Based Music Recommendation. - Elena V. Epure; Gabriel Meseguer-Brocal; Darius Afchar; Romain Hennequin (CoRR, 2024)

AI-Generated Music Detection and its Challenges. - Darius Afchar; Gabriel Meseguer-Brocal; Romain Hennequin (ICASSP, 2025)

Familiarizing with Music: Discovery Patterns for Different Music Discovery Needs. - Marta Moscati; Darius Afchar; Markus Schedl; Bruno Sguerra (UMAP, 2025)

A Fourier Explanation of AI-music Artifacts. - Darius Afchar; Gabriel Meseguer-Brocal; Kamil Akesbi; Romain Hennequin (CoRR, 2025)