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Library learning as Bayesian inference
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Classroom Contents
Dreamcoder- Bootstrapping Inductive Program Synthesis With Wake-Sleep Library Learning
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- 1 Intro
- 2 The premise of program induction
- 3 Why program induction?
- 4 Visual programs
- 5 Learning to write code
- 6 Library learning as Bayesian inference
- 7 Library learning as neurally-guided Bayesian inference
- 8 Abstraction Sleep: Growing the library via refactoring
- 9 Neural recognition model guides search
- 10 DreamCoder Domains
- 11 LOGO Turtle Graphics - learning an interpretable library
- 12 What does DreamCoder dream of7 (before learning)
- 13 What does DreamCoder dream of7 (after learning)
- 14 What does DreamCoder dream of (after learning)
- 15 Planning to build towers
- 16 Dreams after learning
- 17 Learning dynamics
- 18 Synergy between recognition model and library learning
- 19 Evidence for dreaming bootstrapping better libraries
- 20 Growing languages for vector algebra and physics
- 21 Growing a language for recursive programming
- 22 Lessons
