Artificial Intelligence and Mathematics Research

Mee Seong Im, John Hopkins University, Baltimore, MD, and Tony Shaska, Oakland University, Rochester, MI

Articles Tony Shaska, Artificial neural networks on graded vector spaces Mee Seong Im and Venkat R. Dasari, Computational complexity reduction of deep neural networks Carl Henrik Ek, Oisin Kim and Challenger Mishra, Calabi-Yau metrics through Grassmannian learning and Donaldson's algorithm Jose Luis Crespo, Jaime Gutierrez and Angel Valle, Neural network design options for RNG's verification Mee Seong Im, Clement Kam and Caden Pici, Diagrammatics of information Ilias Kotsireas and Tony Shaska, A neurosymbolic framework for geometric reduction of binary forms Yuta Kambe, Yota Maeda and Tristan Vaccon, Geometric generality of Transformer-based Grobner basis computation Mee Seong Im, Semi-invariants of filtered quiver representations with at most two pathways Elira Curri and Tony Shaska, Polynomials, Galois groups, and database-driven arithmetic