SUPR
Multimodal learning
Dnr:

NAISS 2025/22-117

Type:

NAISS Small Compute

Principal Investigator:

Selpi Selpi

Affiliation:

Chalmers tekniska högskola

Start Date:

2025-02-06

End Date:

2026-03-01

Primary Classification:

10210: Artificial Intelligence

Webpage:

Allocation

Abstract

The resources requested in this proposal shall be used to investigate different aspects of multimodal learning in several PhD projects and master's projects. The different aspects include multimodal fusion architectures, representations, modality imbalances, adaptive fusion, temporal and spatial aspects of data, etc. We shall also take into account data-centric AI approach for multimodal learning.