5 citations · 7 across the 6 of their papers we have counts for
8 papers
Batch Normalization for Neural Networks on Complex Domains
Xuan Son Nguyen, Nistor Grozavu
Riemannian neural networks have proven effective in solving a variety of machine learning tasks. The key to their success lies in the development of principled Riemannian analogs o…
Coliseum project: Correlating climate change data with the behavior of heritage materials
A Cormier, David Roqui, Fabrice Surma +5
Heritage materials are already affected by climate change, and increasing climatic variations reduces the lifespan of monuments. As weathering depends on many factors, it is also d…
Siegel Neural Networks
Xuan Son Nguyen, Aymeric Histace, Nistor Grozavu
Riemannian symmetric spaces (RSS) such as hyperbolic spaces and symmetric positive definite (SPD) manifolds have become popular spaces for representation learning. In this paper, w…
A Multimodal Approach to Heritage Preservation in the Context of Climate Change
David Roqui, Adèle Cormier, nistor Grozavu +1
Cultural heritage sites face accelerating degradation due to climate change, yet tradi- tional monitoring relies on unimodal analysis (visual inspection or environmental sen- sors…
CADMR: Cross-Attention and Disentangled Learning for Multimodal Recommender Systems
Yasser Khalafaoui, Martino Lovisetto, Basarab Matei +1
The increasing availability and diversity of multimodal data in recommender systems offer new avenues for enhancing recommendation accuracy and user satisfaction. However, these sy…
Deep Matrix Factorization with Adaptive Weights for Multi-View Clustering
Yasser Khalafaoui, Basarab Matei, Martino Lovisetto +1
Recently, deep matrix factorization has been established as a powerful model for unsupervised tasks, achieving promising results, especially for multi-view clustering. However, exi…
Joint Multi-View Collaborative Clustering
Yasser Khalafaoui, Basarab Matei, Nistor Grozavu +1
Data is increasingly being collected from multiple sources and described by multiple views. These multi-view data provide richer information than traditional single-view data. Fusi…
Multi-modal Multi-view Clustering based on Non-negative Matrix Factorization
Yasser Khalafaoui, Nistor Grozavu, Basarab Matei +1
By combining related objects, unsupervised machine learning techniques aim to reveal the underlying patterns in a data set. Non-negative Matrix Factorization (NMF) is a data mining…