Zobrazeno 1 - 10
of 7 580
pro vyhledávání: '"WANG, Ran"'
Autor:
Xu, Cheng, Zhang, Changtian, Shi, Yuchen, Wang, Ran, Duan, Shihong, Wan, Yadong, Zhang, Xiaotong
Recent advancements in reinforcement learning have made significant impacts across various domains, yet they often struggle in complex multi-agent environments due to issues like algorithm instability, low sampling efficiency, and the challenges of e
Externí odkaz:
http://arxiv.org/abs/2408.11416
Autor:
Zhou, Dazhi, Greve, Thomas R., Gullberg, Bitten, Lee, Minju M., Di Mascolo, Luca, Dicker, Simon R., Romero, Charles E., Chapman, Scott C., Chen, Chian-Chou, Cornish, Thomas, Devlin, Mark J., Ho, Luis C., Kohno, Kotaro, Lagos, Claudia D. P., Mason, Brian S., Mroczkowski, Tony, Wagg, Jeff F. W., Wang, Q. Daniel, Wang, Ran, Brinch, Malte., Dannerbauer, Helmut, Jiang, Xue-Jian, Lauritsen, Lynge R. B., Vijayan, Aswin P., Vizgan, David, Wardlow, Julie L., Sarazin, Craig L., Sarmiento, Karen P., Serjeant, Stephen, Bhandarkar, Tanay A., Haridas, Saianeesh K., Moravec, Emily, Orlowski-Scherer, John, Sievers, Jonathan L. R., Tanaka, Ichi, Wang, Yu-Jan, Zeballos, Milagros, Laza-Ramos, Andres, Liu, Yuanqi, Hassan, Mohd Shaiful Rizal, Jwel, Abdul Kadir Md, Nazri, Affan Adly, Lim, Ming-Kang, Ibrahim, Ungku Ferwani Salwa Ungku
High-redshift radio(-loud) galaxies (H$z$RGs) are massive galaxies with powerful radio-loud active galactic nuclei (AGNs) and serve as beacons for protocluster identification. However, the interplay between H$z$RGs and the large-scale environment rem
Externí odkaz:
http://arxiv.org/abs/2408.02177
Online job advertisements on various job portals or websites have become the most popular way for people to find potential career opportunities nowadays. However, the majority of these job sites are limited to offering fundamental filters such as job
Externí odkaz:
http://arxiv.org/abs/2408.01989
This paper proposes a weight-aware deep reinforcement learning (WADRL) approach designed to address the multiobjective vehicle routing problem with time windows (MOVRPTW), aiming to use a single deep reinforcement learning (DRL) model to solve the en
Externí odkaz:
http://arxiv.org/abs/2407.13113
Let $\{X(t)\}_{t\geqslant0}$ be the generalized fractional Brownian motion introduced by Pang and Taqqu (2019): \begin{align*} \{X(t)\}_{t\ge0}\overset{d}{=}&\left\{ \int_{\mathbb R} \left((t-u)_+^{\alpha}-(-u)_+^{\alpha} \right) |u|^{-\gamma/2} B(du
Externí odkaz:
http://arxiv.org/abs/2405.11851
This work introduces a novel value decomposition algorithm, termed \textit{Dynamic Deep Factor Graphs} (DDFG). Unlike traditional coordination graphs, DDFG leverages factor graphs to articulate the decomposition of value functions, offering enhanced
Externí odkaz:
http://arxiv.org/abs/2405.05542
Semi-supervised symmetric non-negative matrix factorization (SNMF) utilizes the available supervisory information (usually in the form of pairwise constraints) to improve the clustering ability of SNMF. The previous methods introduce the pairwise con
Externí odkaz:
http://arxiv.org/abs/2405.02688
Autor:
Wang, Feige, Yang, Jinyi, Fan, Xiaohui, Venemans, Bram, Decarli, Roberto, Bañados, Eduardo, Walter, Fabian, Barth, Aaron J., Bian, Fuyan, Davies, Frederick B., Eilers, Anna-Christina, Farina, Emanuele Paolo, Hennawi, Joseph F., Li, Jiang-Tao, Mazzucchelli, Chiara, Wang, Ran, Wu, Xue-Bing, Yue, Minghao
The [CII] 158 $\mu$m emission line and the underlying far-infrared (FIR) dust continuum are important tracers for studying star formation and kinematic properties of early galaxies. We present a survey of the [CII] emission lines and FIR continua of
Externí odkaz:
http://arxiv.org/abs/2404.15413
Autor:
Wang, Jing, Lin, Xuchen, Yang, Dong, Staveley-Smith, Lister, Walter, Fabian, Wang, Q. Daniel, Wang, Ran, Battisti, A. J., Catinella, Barbara, Chen, Hsiao-Wen, Cortese, Luca, Fisher, D. B., Ho, Luis C., Ji, Suoqing, Jiang, Peng, Kauffmann, Guinevere, Kong, Xu, Liu, Ziming, Shao, Li, Wang, Jie, Wang, Lile, Wang, Shun
We present a statistical study of the properties of diffuse HI in ten nearby galaxies, comparing the HI detected by the single-dish telescope FAST (FEASTS program) and the interferometer VLA (THINGS program), respectively. The THINGS' observation mis
Externí odkaz:
http://arxiv.org/abs/2404.09422
Autor:
Ge, Fuchun, Wang, Ran, Qu, Chen, Zheng, Peikun, Nandi, Apurba, Conte, Riccardo, Houston, Paul L., Bowman, Joel M., Dral, Pavlo O.
Machine learning potentials (MLPs) are widely applied as an efficient alternative way to represent potential energy surfaces (PES) in many chemical simulations. The MLPs are often evaluated with the root-mean-square errors on the test set drawn from
Externí odkaz:
http://arxiv.org/abs/2403.11216