Lecture 3.1 - Multimodal Representation Fusion (CMU Multimodal Machine Learning, Fall 2023) скачать в хорошем качестве

Lecture 3.1 - Multimodal Representation Fusion (CMU Multimodal Machine Learning, Fall 2023)

Lecture 3.1 - Multimodal Representation Fusion (CMU Multimodal Machine Learning, Fall 2023) Topics: multimodal fusion, cross-model interaction ---------------------------------------------------------------------------------------------------------------- Carnegie Mellon University, 11-777 Multimodal Machine Learning, 2023 Fall Website: https://cmu-multicomp-lab.github.io/m... Instructor: Louis-Philippe Morency Co-lecturer: Paul Liang This revised version of CMU Multimodal Machine Learning course presents the fundamental mathematical concepts in machine learning and deep learning relevant to the six main challenges in multimodal research: (1) representation, (2) alignment, (3) reasoning, (4) generation, (5) transference and (6) quantification. This revised course is based on the new taxonomy introduced in this survey paper: https://arxiv.org/abs/2209.03430