Zobrazeno 1 - 10
of 731
pro vyhledávání: '"Liu, Tie‐Yan"'
The accurate prediction of geometric state evolution in complex systems is critical for advancing scientific domains such as quantum chemistry and material modeling. Traditional experimental and computational methods face challenges in terms of envir
Externí odkaz:
http://arxiv.org/abs/2410.24220
Autor:
He, Liang, Jin, Peiran, Min, Yaosen, Xie, Shufang, Wu, Lijun, Qin, Tao, Liang, Xiaozhuan, Gao, Kaiyuan, Jiang, Yuliang, Liu, Tie-Yan
Proteins, essential to biological systems, perform functions intricately linked to their three-dimensional structures. Understanding the relationship between protein structures and their amino acid sequences remains a core challenge in protein modeli
Externí odkaz:
http://arxiv.org/abs/2410.24022
Autor:
Ren, Yuxuan, Zheng, Dihan, Liu, Chang, Jin, Peiran, Shi, Yu, Huang, Lin, He, Jiyan, Luo, Shengjie, Qin, Tao, Liu, Tie-Yan
In recent years, machine learning has demonstrated impressive capability in handling molecular science tasks. To support various molecular properties at scale, machine learning models are trained in the multi-task learning paradigm. Nevertheless, dat
Externí odkaz:
http://arxiv.org/abs/2410.10118
As a popular form of knowledge and experience, patterns and their identification have been critical tasks in most data mining applications. However, as far as we are aware, no study has systematically examined the dynamics of pattern values and their
Externí odkaz:
http://arxiv.org/abs/2409.04456
Molecular modeling, a central topic in quantum mechanics, aims to accurately calculate the properties and simulate the behaviors of molecular systems. The molecular model is governed by physical laws, which impose geometric constraints such as invari
Externí odkaz:
http://arxiv.org/abs/2406.16853
Autor:
Zhang, He, Liu, Chang, Wang, Zun, Wei, Xinran, Liu, Siyuan, Zheng, Nanning, Shao, Bin, Liu, Tie-Yan
Predicting the mean-field Hamiltonian matrix in density functional theory is a fundamental formulation to leverage machine learning for solving molecular science problems. Yet, its applicability is limited by insufficient labeled data for training. I
Externí odkaz:
http://arxiv.org/abs/2403.09560
Autor:
Pei, Qizhi, Gao, Kaiyuan, Wu, Lijun, Zhu, Jinhua, Xia, Yingce, Xie, Shufang, Qin, Tao, He, Kun, Liu, Tie-Yan, Yan, Rui
Modeling the interaction between proteins and ligands and accurately predicting their binding structures is a critical yet challenging task in drug discovery. Recent advancements in deep learning have shown promise in addressing this challenge, with
Externí odkaz:
http://arxiv.org/abs/2310.06763
Autor:
Fang, Yuchen, Tang, Zhenggang, Ren, Kan, Liu, Weiqing, Zhao, Li, Bian, Jiang, Li, Dongsheng, Zhang, Weinan, Yu, Yong, Liu, Tie-Yan
Order execution is a fundamental task in quantitative finance, aiming at finishing acquisition or liquidation for a number of trading orders of the specific assets. Recent advance in model-free reinforcement learning (RL) provides a data-driven solut
Externí odkaz:
http://arxiv.org/abs/2307.03119