Zobrazeno 1 - 10
of 24 738
pro vyhledávání: '"SUN, Yan"'
Autor:
Bao, Ergen, Zhao, Jinbin, Gao, Qiang, Shahid, Ijaz, Ma, Hui, Luo, Yixiu, Liu, Peitao, Sun, Yan, Chen, Xing-Qiu
Nitriding introduces nitrides into the surface of steels, significantly enhancing the surface me-chanical properties. By combining the variable composition evolutionary algorithm and first-principles calculations based on density functional theory, 5
Externí odkaz:
http://arxiv.org/abs/2411.17193
Large Language Models (LLMs) have revolutionized natural language processing (NLP) by delivering state-of-the-art performance across a variety of tasks. Among these, Transformer-based models like BERT and GPT rely on pooling layers to aggregate token
Externí odkaz:
http://arxiv.org/abs/2411.14654
Averaging iterations of Stochastic Gradient Descent (SGD) have achieved empirical success in training deep learning models, such as Stochastic Weight Averaging (SWA), Exponential Moving Average (EMA), and LAtest Weight Averaging (LAWA). Especially, w
Externí odkaz:
http://arxiv.org/abs/2411.13169
The capture of changes in dynamic systems, especially ordinary differential equations (ODEs), is an important and challenging task, with multiple applications in biomedical research and other scientific areas. This article proposes a fast and mathema
Externí odkaz:
http://arxiv.org/abs/2411.12277
Autor:
Sun, Yan, Yang, Ji, Zhang, Shaobo, Yan, Qing-Zeng, Su, Yang, Chen, Xuepeng, Zhou, Xin, Xu, Ye, Wang, Hongchi, Wang, Min, Jiang, Zhibo, Sun, Ji-Xian, Lu, Deng-Rong, Ju, Bing-Gang, Zhang, Xu-Guo
Based on 32162 molecular clouds from the Milky Way Imaging Scroll Painting project, we obtain new face-on molecular gas maps of the northern outer Galaxy. The total molecular gas surface density map reveals three segments of spirals, extending 16-43
Externí odkaz:
http://arxiv.org/abs/2411.11220
Minimax optimization is gaining increasing attention in modern machine learning applications. Driven by large-scale models and massive volumes of data collected from edge devices, as well as the concern to preserve client privacy, communication-effic
Externí odkaz:
http://arxiv.org/abs/2411.09365
Autor:
Wang, Jiantao, Liu, Peitao, Zhu, Heyu, Liu, Mingfeng, Ma, Hui, Chen, Yun, Sun, Yan, Chen, Xing-Qiu
Combining the efficiency of semi-empirical potentials with the accuracy of quantum mechanical methods, machine-learning interatomic potentials (MLIPs) have significantly advanced atomistic modeling in computational materials science and chemistry. Th
Externí odkaz:
http://arxiv.org/abs/2411.01282
Large pretrained transformer models have revolutionized modern AI applications with their state-of-the-art performance in natural language processing (NLP). However, their substantial parameter count poses challenges for real-world deployment. To add
Externí odkaz:
http://arxiv.org/abs/2411.00969
Autor:
Li, Yuping, Liu, Mingfeng, Li, Jiangxu, Wang, Jiantao, Lai, Junwen, He, Dongchang, Qiu, Ruizhi, Sun, Yan, Chen, Xing-Qiu, Liu, Peitao
Publikováno v:
Phys. Rev. B 110, 195118 (2024)
Recently, a first-order phase transition associated with charge density wave (CDW) has been observed at low temperatures in intermetallic compound BaFe$_2$Al$_9$. However, this transition is absent in its isostructural sister compound BaCo$_2$Al$_9$.
Externí odkaz:
http://arxiv.org/abs/2410.22734
In recent years, Transformer-based models (Transformers) have achieved significant success in multivariate time series forecasting (MTSF). However, previous works focus on extracting features either from the time domain or the frequency domain, which
Externí odkaz:
http://arxiv.org/abs/2410.22649