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Data-driven OLED candidate design: a generative model from independent-property domains to the comprehensive performance enhancement

Application of self-supervised learning in steel surface defect detection

A critical review of machine learning interatomic potentials and Hamiltonian

Accelerating phase-field simulation of coupled microstructural evolution using autoencoder-based recurrent neural networks

Machine learning for predictive design and optimization of high-performance thermoelectric materials: a review

DSMR: an AI framework for exploring combinations of data and algorithm to overcome efficiency-accuracy trade-off

Farthest point sampling in property designated chemical feature space as an effective strategy for enhancing the machine learning model performance for small scale chemical dataset

Effects of nonlinearity and inter-feature coupling in machine learning studies of Nb alloys with center-environment features

Exploring generic fractions of multi-origin asphalts and revisiting the linkage to their bulk properties via machine learning

Machine learning-enabled optoelectronic material discovery: a comprehensive review

Active learning-based generative design of halogen-free flame-retardant polymeric composites

Neuroevolution potential for thermal transport in silicon carbide