Multimodal learning is a fascinating area of research that focuses on the integration of information from multiple sources. Below is a curated list of papers related to multimodal learning that you might find interesting.
Deep Learning for Multimodal Data Fusion: This paper explores the use of deep learning techniques for fusing information from different modalities.
A Survey of Multimodal Learning Techniques: A comprehensive survey of various multimodal learning techniques and their applications.
Multimodal Learning with Generative Adversarial Networks: This paper discusses the application of GANs in multimodal learning scenarios.
Multimodal Fusion for Image Recognition: A study on how to effectively fuse multimodal information for image recognition tasks.
For more resources on multimodal learning, you can visit our Multimodal Learning Resources.
Here's an image of a neural network, which is at the heart of multimodal learning: