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- What would it take to build an AI bench scientist
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Classroom Contents
A Tutorial on Causal Representation Learning
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- 1 - Intro
- 2 - How we got here
- 3 - What would it take to build an AI bench scientist
- 4 - The setup
- 5 - The challenge of nonlinearity
- 6 - No causal representations without assumptions
- 7 - Time contrastive learning
- 8 - Switchover: Dhanya Sridhar
- 9 - What other learning signals can we use?
- 10 - Tree-based regularization
- 11 - Sparse mechanisms
- 12 - Multiple views and sparsity
- 13 - Concluding questions
