108 citations · 108 across the 5 of their papers we have counts for
5 papers
Machine Learning Accelerated SSNEB for Efficient Minimum Energy Pathway Calculations
Yu Zhang, Guanzhi Li, Minkyung Han +4
Metastable states and their minimum energy pathways (MEPs) are central to understanding transformations and phase stability in complex materials, yet mapping transition pathways be…
MatterSim-MT: A multi-task foundation model for in silico materials characterization
Han Yang, Xixian Liu, Chenxi Hu +25
Accurate property characterization is a major bottleneck in materials design. While first-principles methods and task-specific machine-learning models have driven important progres…
ShapeCond: Fast Shapelet-Guided Dataset Condensation for Time Series Classification
Sijia Peng, Yun Xiong, Xi Chen +5
Time series data supports many domains (e.g., finance and climate science), but its rapid growth strains storage and computation. Dataset condensation can alleviate this by synthes…
Probing the Limit of Heat Transfer in Inorganic Crystals with Deep Learning
Jielan Li, Zekun Chen, Qian Wang +21
Heat transfer is a fundamental property of matter. Research spanning decades has attempted to discover materials with exceptional thermal conductivity, yet the upper limit remains…
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Han Yang, Chenxi Hu, Yichi Zhou +19
Accurate and fast prediction of materials properties is central to the digital transformation of materials design. However, the vast design space and diverse operating conditions p…