Videos

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Gyorgy Turan - Error-correcting codes: a sandbox for learning, interpretability and optimization

September 2, 2026
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Gal Mishne - From Explanations to Mechanisms: Interpreting Computation in Graph Neural Networks

September 2, 2026
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Elias Bareinboim - Towards Causal AI: From Mechanism to Understanding

September 2, 2026
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Michael Winer - Mechanistic Understanding of Multilayer Perceptrons

September 2, 2026
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Yusu Wang - Neural Network Generalization through an algorithmic lens

September 2, 2026
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Sam Eisenstat - Concepts, information, and objectivity

September 2, 2026
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Christopher Potts - Creating and detecting subliminal learning effects on demand

September 1, 2026
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Ryan Cotterell - Two views of a language model

September 1, 2026
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Jacob Steinhardt - Oversight Foundation Models

September 1, 2026
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Max Tegmark - Neural network interpretability: symmetry, geometry and formal verification

September 1, 2026
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Bin Yu - Not All Interpretation Methods Are Created Equal: Principled Evaluation of AI Interpretability

September 1, 2026
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Josh Batson - Interpretability: From Art Towards Science

August 31, 2026
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