Introduces dualGNN, an autoregressive message-passing GNN using signed circuits to sample uniform fine regular triangulations of lattice polytopes, applied to Calabi-Yau threefolds at h^{1,1}=86 and 128.
Counting calabi-yau threefolds,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Phenomenological late-time vacuum-tunneling models are fit to DESI DR2, supernova, and CMB data, allowing up to 50% vacuum-energy drop for z_t < 1 and a preferred z_t ~7 model that converts ~10% dark matter while easing cosmological tensions.
citing papers explorer
-
Sampling Triangulations and Calabi-Yau Threefolds with Autoregressive GNNs
Introduces dualGNN, an autoregressive message-passing GNN using signed circuits to sample uniform fine regular triangulations of lattice polytopes, applied to Calabi-Yau threefolds at h^{1,1}=86 and 128.