Multimodal and Cross-Modal Learning Techniques
Multimodal data fusion is increasingly becoming relevant in machine learning, enabling richer, more comprehensive, and robust models. This is achieved by effectively integrating diverse data types including images, text, audio, sensor signals, and scientific datasets (e.g., crystallographic, spectroscopic, and electronic properties measurements). This special issue invites original research articles and reviews focusing on cutting-edge advancements in multimodal alignments and cross-modal learning techniques. Submissions are encouraged to explore novel methodologies, theoretical foundations, and practical implementations addressing key challenges in multimodal integration, such as handling modality heterogeneity, scalability, interpretability, and representation learning across diverse data sources.
Topics covered include, but are not limited to:
- Multimodal data fusion
- Multimodal integration
- Cross-modal learning
- Multimodal alignments
- Machine Learning
- Novel architectures and algorithms for latent space alignment
- Cross-modal representation learning and transfer learning methods
- Approaches to managing modality imbalance and heterogeneity
- Scalability and efficiency improvements in multimodal models
- Interpretability and explainability techniques for multimodal systems
- Advanced neural network architectures for multimodal fusion
- Practical applications and case studies demonstrating multimodal integration
- Robotics and autonomous systems leveraging multimodal data
- Human-computer interaction enhancements through multimodal techniques
- Physics-informed multimodal learning techniques
- Multimodal fusion for materials property prediction and discovery
- Machine learning integration with spectroscopy and microscopy data
- Multimodal approaches to computational materials science
- AI-driven discovery and design of advanced functional materials
Guest Editors
Anand Babu, Université catholique de Louvain (UCLouvain)
N. M. Anoop Krishnan, Indian Institute of Technology (IIT) Delhi