Unsupervised learning for improving fault detection in complex systems. - Roy Assaf; Samia Nefti-Meziani; Philip A. Scarf (AIM, 2017)

Diagnosis for systems with multi-component wear interactions. - Roy Assaf; Phuc Do; Philip Scarf; Samia Nefti-Meziani (ICPHM, 2017)

Towards a practical implementation of EIT-based sensors using artificial neural networks. - Stefania Russo; Roy Assaf; Samia Nefti-Meziani (IEEE SENSORS, 2017)

MTEX-CNN: Multivariate Time Series EXplanations for Predictions with Convolutional Neural Networks. - Roy Assaf; Ioana Giurgiu; Frank Bagehorn; Anika Schumann (ICDM, 2019)

Explainable Deep Neural Networks for Multivariate Time Series Predictions. - Roy Assaf; Anika Schumann (IJCAI, 2019)

Modelling and application of condition-based maintenance for a two-component system with stochastic and economic dependencies. - Phuc Do; Roy Assaf; Philip A. Scarf; Benoît Iung (Reliab. Eng. Syst. Saf., 2019)

An Anomaly Detection and Explainability Framework using Convolutional Autoencoders for Data Storage Systems. - Roy Assaf; Ioana Giurgiu; Jonas Pfefferle; Serge Monney; Haris Pozidis; Anika Schumann (IJCAI, 2020)

Probabilistic Feature Matching for Fast Scalable Visual Prompting. - Thomas Frick; Cezary Skura; Filip Janicki; Roy Assaf; Niccolò Avogaro; Daniel Caraballo; Yagmur Gizem Cinar; Brown Ebouky; Ioana Giurgiu; Takayuki Katsuki; Piotr Kluska; Cristiano Malossi; et al. (IJCAI, 2024)

Show or Tell? Effectively prompting Vision-Language Models for semantic segmentation. - Niccolò Avogaro; Thomas Frick; Mattia Rigotti; Andrea Bartezzaghi; Filip Janicki; A. Cristiano I. Malossi; Konrad Schindler; Roy Assaf (Trans. Mach. Learn. Res., 2025)

VP Lab: a PEFT-Enabled Visual Prompting Laboratory for Semantic Segmentation. - Niccolò Avogaro; Thomas Frick; Yagmur Gizem Cinar; Daniel Caraballo; Cezary Skura; Filip Janicki; Piotr Kluska; Brown Ebouky; Nicola Farronato; Florian Scheidegger; Cristiano Malossi; Konrad Schindler; et al. (CoRR, 2025)