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- Introductions & Opening
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- Outline
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- Motivation: ML for Scientific Discovery
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- Unwarranted Optimism About Deep Generative Models
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- Our Results: Possibility Theorem
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- Conclusions
Description:
Explore a thought-provoking conference talk on scientific discovery and unsupervised disentanglement delivered by Professor Yair Weiss from the Hebrew University. Delve into the intersection of machine learning, computer vision, and neural computation as Weiss challenges unwarranted optimism about deep generative models. Examine the motivation behind using machine learning for scientific discovery, and uncover the speaker's groundbreaking results on possibility theorems. Gain valuable insights into the potential and limitations of AI in advancing scientific understanding, concluding with a critical analysis of current approaches and future directions in the field.

Scientific Discovery and Unsupervised Disentanglement - Yair Weiss, PhD

Open Data Science
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