mcarbonell/neural-tablebases

Deep learning approach to chess tablebase compression using geometric position encoding. Achieves 99.93% accuracy on 3-piece endgames with 79.7x compression ratio vs Syzygy format.

22
/ 100
Experimental
No Package No Dependents
Maintenance 13 / 25
Adoption 0 / 25
Maturity 9 / 25
Community 0 / 25

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Language

Python

License

MIT

Category

board-game-ai-engines

Last pushed

Mar 21, 2026

Commits (30d)

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Board Game AI Engines · 144 frameworks

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