Roy Assaf

According to our database, Roy Assaf authored at least 8 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Probabilistic Feature Matching for Fast Scalable Visual Prompting.

Thomas Frick, Cezary Skura, Filip Janicki, Roy Assaf, Niccolo Avogaro, Daniel Caraballo, Yagmur Gizem Cinar, Brown Ebouky, Ioana Giurgiu, Takayuki Katsuki, Piotr Kluska, Cristiano Malossi, Haoxiang Qiu, Tomoya Sakai, Florian Scheidegger, Andrej Simeski, Daniel Yang, Andrea Bartezzaghi, Mattia Rigotti

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2020

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

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

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

Explainable Deep Neural Networks for Multivariate Time Series Predictions.

Roy Assaf, Anika Schumann

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

MTEX-CNN: Multivariate Time Series EXplanations for Predictions with Convolutional Neural Networks.

Roy Assaf, Ioana Giurgiu, Frank Bagehorn, Anika Schumann

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2017

Towards a practical implementation of EIT-based sensors using artificial neural networks.

Stefania Russo, Roy Assaf, Samia Nefti-Meziani

Proceedings of the 2017 IEEE SENSORS, Glasgow, United Kingdom, October 29, 2017

Diagnosis for systems with multi-component wear interactions.

Roy Assaf, Phuc Do, Philip Scarf, Samia Nefti-Meziani

Proceedings of the 2017 IEEE International Conference on Prognostics and Health Management, 2017

Unsupervised learning for improving fault detection in complex systems.

Roy Assaf, Samia Nefti-Meziani, Philip A. Scarf

Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics, 2017