22 citations · 29 across the 8 of their papers we have counts for
4 papers · 1 filter
MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning
Paul Pu Liang, Yiwei Lyu, Xiang Fan +4
Learning multimodal representations involves integrating information from multiple heterogeneous sources of data. In order to accelerate progress towards understudied modalities an…
Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications
Paul Pu Liang, Chun Kai Ling, Yun Cheng +6
In many machine learning systems that jointly learn from multiple modalities, a core research question is to understand the nature of multimodal interactions: how modalities combin…
Multimodal Fusion Interactions: A Study of Human and Automatic Quantification
Paul Pu Liang, Yun Cheng, Ruslan Salakhutdinov +1
In order to perform multimodal fusion of heterogeneous signals, we need to understand their interactions: how each modality individually provides information useful for a task and…
Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework
Paul Pu Liang, Yun Cheng, Xiang Fan +9
The recent explosion of interest in multimodal applications has resulted in a wide selection of datasets and methods for representing and integrating information from different mod…