2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.LG2024★ 2 cited
MixMAS: A Framework for Sampling-Based Mixer Architecture Search for Multimodal Fusion and Learning
Abdelmadjid Chergui, Grigor Bezirganyan, Sana Sellami +2
Choosing a suitable deep learning architecture for multimodal data fusion is a challenging task, as it requires the effective integration and processing of diverse data types, each…
cs.LG2024
Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion
Grigor Bezirganyan, Sana Sellami, Laure Berti-Équille +1
Multimodal AI models are increasingly used in fields like healthcare, finance, and autonomous driving, where information is drawn from multiple sources or modalities such as images…