85 citations · 181 across the 9 of their papers we have counts for
9 papers
A Physical Response-and-Memory Model for Muon Optimization
Yinze Hu, Hongjun Xiang, Xingao Gong +1
Training large language models is costly. How low a loss the same compute can ultimately reach depends on how each step's gradient is converted into a weight update; the rule that…
Accelerating the electronic-structure calculation of magnetic systems by equivariant neural networks
Yang Zhong, Binhua Zhang, Hongyu Yu +2
Complex spin-spin interactions in magnets can often lead to magnetic superlattices with complex local magnetic arrangements, and many of the magnetic superlattices have been found…
Capturing long-range interaction with reciprocal space neural network
Hongyu Yu, Liangliang Hong, Shiyou Chen +2
Machine Learning (ML) interatomic models and potentials have been widely employed in simulations of materials. Long-range interactions often dominate in some ionic systems whose dy…
General time-reversal equivariant neural network potential for magnetic materials
Hongyu Yu, Boyu Liu, Yang Zhong +5
This study introduces time-reversal E(3)-equivariant neural network and SpinGNN++ framework for constructing a comprehensive interatomic potential for magnetic systems, encompassin…
Transferable E(3) equivariant parameterization for Hamiltonian of molecules and solids
Yang Zhong, Hongyu Yu, Mao Su +2
Using the message-passing mechanism in machine learning (ML) instead of self-consistent iterations to directly build the mapping from structures to electronic Hamiltonian matrices…
Spin-Dependent Graph Neural Network Potential for Magnetic Materials
Hongyu Yu, Yang Zhong, Liangliang Hong +4
The development of machine learning interatomic potentials has immensely contributed to the accuracy of simulations of molecules and crystals. However, creating interatomic potenti…
DelTact: A Vision-based Tactile Sensor Using Dense Color Pattern
Guanlan Zhang, Yipai Du, Hongyu Yu +1
Tactile sensing is an essential perception for robots to complete dexterous tasks. As a promising tactile sensing technique, vision-based tactile sensors have been developed to imp…
Edge-based Tensor prediction via graph neural networks
Yang Zhong, Hongyu Yu, Xingao Gong +1
Message-passing neural networks (MPNN) have shown extremely high efficiency and accuracy in predicting the physical properties of molecules and crystals, and are expected to become…
Complex Spin Hamiltonian Represented by Artificial Neural Network
Hongyu Yu, Changsong Xu, Feng Lou +4
The effective spin Hamiltonian method is widely adopted to simulate and understand the behavior of magnetism. However, the magnetic interactions of some systems, such as itinerant…