Zobrazeno 1 - 10
of 1 537
pro vyhledávání: '"Meisen, A."'
In this article, we investigate some problems about the initial-value problem of the focusing Ablowitz-Ladik system, and the initial data belongs to a discrete weighted $\ell^2$ space. On the one hand, we have proved the global well-posedness for the
Externí odkaz:
http://arxiv.org/abs/2407.21526
This technical report outlines our method for generating a synthetic dataset for semantic segmentation using a latent diffusion model. Our approach eliminates the need for additional models specifically trained on segmentation data and is part of our
Externí odkaz:
http://arxiv.org/abs/2406.17541
Autor:
de Puiseau, Constantin Waubert, Dörpelkus, Christian, Peters, Jannik, Tercan, Hasan, Meisen, Tobias
Learned construction heuristics for scheduling problems have become increasingly competitive with established solvers and heuristics in recent years. In particular, significant improvements have been observed in solution approaches using deep reinfor
Externí odkaz:
http://arxiv.org/abs/2406.07325
Autor:
Hahn, Yannik, Maack, Robert, Buchholz, Guido, Purrio, Marion, Angerhausen, Matthias, Tercan, Hasan, Meisen, Tobias
The digitization of manufacturing processes enables promising applications for machine learning-assisted quality assurance. A widely used manufacturing process that can strongly benefit from data-driven solutions is gas metal arc welding (GMAW). The
Externí odkaz:
http://arxiv.org/abs/2310.12632
Solving job shop scheduling problems (JSSPs) with a fixed strategy, such as a priority dispatching rule, may yield satisfactory results for several problem instances but, nevertheless, insufficient results for others. From this single-strategy perspe
Externí odkaz:
http://arxiv.org/abs/2305.10192
Autor:
de Puiseau, Constantin Waubert, Peters, Jannik, Dörpelkus, Christian, Tercan, Hasan, Meisen, Tobias
Research on deep reinforcement learning (DRL) based production scheduling (PS) has gained a lot of attention in recent years, primarily due to the high demand for optimizing scheduling problems in diverse industry settings. Numerous studies are carri
Externí odkaz:
http://arxiv.org/abs/2301.04182
In reinforcement learning (RL) research, simulations enable benchmarks between algorithms, as well as prototyping and hyper-parameter tuning of agents. In order to promote RL both in research and real-world applications, frameworks are required which
Externí odkaz:
http://arxiv.org/abs/2212.00906
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 19, Iss 1, Pp 135-151 (2024)
Alongside natural language processing and computer vision, large learning models have found their way into e-commerce. Especially, for recommender systems and click-through rate prediction, these models have shown great predictive power. In this work
Externí odkaz:
https://doaj.org/article/ea7b54d3deca485ba634147ef12d7a7f
Recasting phenomenological Lagrangians in terms of SM effective field theory (SMEFT) provides a valuable means of connecting potential BSM physics at momenta well above the electroweak scale to experimental signatures at lower energies. In this work
Externí odkaz:
http://arxiv.org/abs/2211.01094
Autor:
Yifan Wang, Lei Xie, Ke Wang, Zixi Jiang, Yuhang Feng, Yao Yu, Xin Chang, Hailiang Meng, Yiran Xu, Yishan Wu, Meisen Shi, Xiaoxia Wang, Shaoqing Wen
Publikováno v:
Frontiers in Ecology and Evolution, Vol 12 (2024)
IntroductionThe Xinjiang Mongolians, located along the Silk Road, migrated westward from Northeast Asia in the 13th and 14th centuries. Despite its significance, genetic studies on Xinjiang Mongolians have been limited compared to other Mongolian pop
Externí odkaz:
https://doaj.org/article/4d190a2b13b84cbaa2d7617dc311d924