Lecture 7.2 - Multimodal Inference and Knowledge (CMU Multimodal Machine Learning, Fall 2023)

Lecture 7.2 - Multimodal Inference and Knowledge (CMU Multimodal Machine Learning, Fall 2023) Topics: structure discovery, language and discrete concepts, causal inference, external knowledge, reasoning ---------------------------------------------------------------------------------------------------------------- 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

Lecture 9.1 - Multimodal Generation (CMU Multimodal Machine Learning, Fall 2023)
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Lecture 9.1 - Multimodal Generation (CMU Multimodal Machine Learning, Fall 2023)

Lecture 2.1 - Unimodal Representation - Part1 (CMU Multimodal Machine Learning, Fall 2023)
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Lecture 2.1 - Unimodal Representation - Part1 (CMU Multimodal Machine Learning, Fall 2023)

[CVPR 2026] 1st Workshop on Generative 3D Reconstruction - Christian Rupprecht
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[CVPR 2026] 1st Workshop on Generative 3D Reconstruction - Christian Rupprecht

RI Seminar: Max Simchowitz: Generative Control, Action Chunking, and Moravec’s Paradox
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RI Seminar: Max Simchowitz: Generative Control, Action Chunking, and Moravec’s Paradox

GNN Explanations that do not Explain and Hot to Find Them
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GNN Explanations that do not Explain and Hot to Find Them

Quantum BC Seminar Series on August 12, 2025: Elham Torabian and Jonas Jäger
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Quantum BC Seminar Series on August 12, 2025: Elham Torabian and Jonas Jäger

Lecture 7.1 - Multimodal Interaction (CMU Multimodal Machine Learning, Fall 2023)
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Lecture 7.1 - Multimodal Interaction (CMU Multimodal Machine Learning, Fall 2023)

Lecture 11.2 - Transference - Part2 (CMU Multimodal Machine Learning, Fall 2023)
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Lecture 11.2 - Transference - Part2 (CMU Multimodal Machine Learning, Fall 2023)

Andrew Ng: Opportunities in AI - 2023
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Andrew Ng: Opportunities in AI - 2023

Bayes theorem, the geometry of changing beliefs
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Bayes theorem, the geometry of changing beliefs

MIT Just Revealed the AI Bubble's Fatal Flaw
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MIT Just Revealed the AI Bubble's Fatal Flaw

Lecture 5.1 - Multimodal Transformers - Part1 (CMU Multimodal Machine Learning, Fall 2023)
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Lecture 5.1 - Multimodal Transformers - Part1 (CMU Multimodal Machine Learning, Fall 2023)

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

How To Think SO CLEARLY People Assume You're A Genius
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How To Think SO CLEARLY People Assume You're A Genius

Q-Learning: Model Free Reinforcement Learning and Temporal Difference Learning
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Q-Learning: Model Free Reinforcement Learning and Temporal Difference Learning

Lecture 3.2 - Multimodal Coordination and Fission (CMU Multimodal Machine Learning, Fall 2023)
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Lecture 3.2 - Multimodal Coordination and Fission (CMU Multimodal Machine Learning, Fall 2023)

CMU Advanced NLP Fall 2024 (7): Prompting and Complex Reasoning
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CMU Advanced NLP Fall 2024 (7): Prompting and Complex Reasoning

Lecture 4.2 - Aligned Representation (CMU Multimodal Machine Learning, Fall 2023)
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Lecture 4.2 - Aligned Representation (CMU Multimodal Machine Learning, Fall 2023)

CMU Introduction To Deep Learning 11-785, Fall 2025: Lecture 4
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CMU Introduction To Deep Learning 11-785, Fall 2025: Lecture 4

Lecture 4.1 - Multimodal Alignment (CMU Multimodal Machine Learning, Fall 2023)
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Lecture 4.1 - Multimodal Alignment (CMU Multimodal Machine Learning, Fall 2023)