Reinforcement learning finds explicit graph realizations for three of six previously unresolved extreme rays of the N=6 holographic entropy cone and supplies evidence that the other three lie outside it.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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Transformer trained on S10 permutation prediction from transpositions generalizes to S25 with near 100% accuracy using identity augmentation and partitioned windows.
Neural networks classify Seiberg dual classes on Z_m x Z_n orbifolds with R^2=0.988 and predict toric multiplicities for Y^{6,0} with mean absolute error 0.021 under fixed Kasteleyn representative.
citing papers explorer
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Exploring the holographic entropy cone via reinforcement learning
Reinforcement learning finds explicit graph realizations for three of six previously unresolved extreme rays of the N=6 holographic entropy cone and supplies evidence that the other three lie outside it.
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Learning the symmetric group: large from small
Transformer trained on S10 permutation prediction from transpositions generalizes to S25 with near 100% accuracy using identity augmentation and partitioned windows.
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Machine Learning Toric Duality in Brane Tilings
Neural networks classify Seiberg dual classes on Z_m x Z_n orbifolds with R^2=0.988 and predict toric multiplicities for Y^{6,0} with mean absolute error 0.021 under fixed Kasteleyn representative.