Description
Multimodal machine learning (MMML) is a vibrant multi-disciplinary research field which addresses some of the original goals of artificial intelligence by integrating and modeling multiple communicative modalities, including language, vision, and acoustic. This research field brings some unique challenges for multimodal researchers given the heterogeneity of the data and the contingency often found between modalities. This course is designed to be a graduate-level course covering recent research papers in multimodal machine learning, including technical challenges with representation, alignment, reasoning, generation, co-learning and quantifications. The main goal of the course is to increase critical thinking skills, knowledge of recent technical achievements and understanding of future research directions.
General Information
Time
Fridays 10:10am-11:30am
Name | Office Hours | |
---|---|---|
AmirAli Bagher Zadeh | When? Where? | |
Paul Liang | When? Where? | |
Louis-Philippe Morency | When? Where? |
Reading Assignments
Reading Assignments
Due Date
Apr 27, 2022
Apr 20, 2022
Apr 20, 2022
Apr 13, 2022
Mar 30, 2022
Mar 30, 2022
Mar 23, 2022
Mar 23, 2022
Mar 16, 2022
Mar 16, 2022
Feb 23, 2022
Feb 23, 2022
Feb 16, 2022
Feb 16, 2022
Feb 9, 2022
Feb 9, 2022
Feb 2, 2022
Feb 2, 2022
Jan 26, 2022
Jan 26, 2022