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Conclusion
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Classroom Contents
Deep Learning for Symbolic Mathematics
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- 1 Intro
- 2 Neural networks and symbolic reasoning
- 3 Problem statement
- 4 Generating expressions randomly
- 5 Counting number of expressions
- 6 Formulae for counting no. of trees and expressions
- 7 Generating dataset for Integration
- 8 Ordinary Differential Equations (1st order)
- 9 Dataset Cleaning
- 10 Dataset Statistics
- 11 Sequence Decoding
- 12 Evaluation
- 13 Comparison with mathematical frameworks
- 14 Generalization across generators
- 15 Generalization beyond the generator
- 16 Conclusion
