12 citations · 21 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Computing Approximate Graph Edit Distance via Optimal Transport
Qihao Cheng, Da Yan, Tianhao Wu +2
Given a graph pair , graph edit distance (GED) is defined as the minimum number of edit operations converting to . GED is a fundamental operation widely used…
cond-mat.mtrl-sci2024★ 9 cited
Machine Learning and First-Principles Predictions of Materials with Low Lattice Thermal Conductivity
Chia-Min Lin, Abishek Khatri, Da Yan +1
We perform machine learning (ML) simulations and density functional theory (DFT) calculations to search for materials with low lattice thermal conductivity, . Several cadmium…
cond-mat.supr-con2023★ 12 cited
Machine learning the relationship between Debye temperature and superconducting transition temperature
Adam D. Smith, Sumner B. Harris, Renato P. Camata +2
Recently a relationship between the Debye temperature and the superconducting transition temperature of conventional superconductors has been proposed [npj Quantum Mate…