Causal Models
Yoshua Bengio discusses the importance of causal models in machine learning and the ability to deal with dependencies between high-level concepts. He explains the difference between statistical models and causal models, highlighting the role of interventions in determining different distributions. Bengio also explores the Bayesian approach and how it can be made tractable with the use of large neural nets.In this clip
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The Gradient
Yoshua Bengio: The Past, Present, and Future of Deep Learning
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