Zobrazeno 1 - 10
of 103
pro vyhledávání: '"Wang Qizhou"'
Publikováno v:
矿业科学学报, Vol 8, Iss 1, Pp 127-136 (2023)
Based on the current situation of comprehensive utilization of coal slime in China and the urgent need for water pollution control in coal mining areas, this paper uses coal slime(CS)as raw material and CaCl2 as the activator, different proportions o
Externí odkaz:
https://doaj.org/article/b8dd5556c49d4c44b7789831f272c9b2
Publikováno v:
Nanophotonics, Vol 11, Iss 11, Pp 2483-2505 (2021)
Nanophotonics inverse design is a rapidly expanding research field whose goal is to focus users on defining complex, high-level optical functionalities while leveraging machines to search for the required material and geometry configurations in sub-w
Externí odkaz:
https://doaj.org/article/f609d058c7ec45ab846fb8dcd86c1ae0
The compelling goal of eradicating undesirable data behaviors, while preserving usual model functioning, underscores the significance of machine unlearning within the domain of large language models (LLMs). Recent research has begun to approach LLM u
Externí odkaz:
http://arxiv.org/abs/2406.09179
Large vision language models, such as CLIPs, have revolutionized modern machine learning. CLIPs have demonstrated great generalizability under distribution shifts, supported by an increasing body of literature. However, the evaluation datasets for CL
Externí odkaz:
http://arxiv.org/abs/2403.11497
Deep neural networks often face generalization problems to handle out-of-distribution (OOD) data, and there remains a notable theoretical gap between the contributing factors and their respective impacts. Literature evidence from in-distribution data
Externí odkaz:
http://arxiv.org/abs/2312.16243
Autor:
Makarenko, Maksim, Wang, Qizhou, Burguete-Lopez, Arturo, Giancola, Silvio, Ghanem, Bernard, Passone, Luca, Fratalocchi, Andrea
Foundation models, exemplified by GPT technology, are discovering new horizons in artificial intelligence by executing tasks beyond their designers' expectations. While the present generation provides fundamental advances in understanding language an
Externí odkaz:
http://arxiv.org/abs/2312.10639
This paper considers an important Graph Anomaly Detection (GAD) task, namely open-set GAD, which aims to train a detection model using a small number of normal and anomaly nodes (referred to as seen anomalies) to detect both seen anomalies and unseen
Externí odkaz:
http://arxiv.org/abs/2311.06835
Out-of-distribution (OOD) detection discerns OOD data where the predictor cannot make valid predictions as in-distribution (ID) data, thereby increasing the reliability of open-world classification. However, it is typically hard to collect real out-o
Externí odkaz:
http://arxiv.org/abs/2311.03236
Open-world classification systems should discern out-of-distribution (OOD) data whose labels deviate from those of in-distribution (ID) cases, motivating recent studies in OOD detection. Advanced works, despite their promising progress, may still fai
Externí odkaz:
http://arxiv.org/abs/2311.01796
Autor:
Barkey, Martin, Büchner, Rebecca, Wester, Alwin, Pritzl, Stefanie D., Makarenko, Maksim, Wang, Qizhou, Weber, Thomas, Trauner, Dirk, Maier, Stefan A., Fratalocchi, Andrea, Lohmüller, Theobald, Tittl, Andreas
Nanophotonic devices excel at confining light into intense hot spots of the electromagnetic near fields, creating unprecedented opportunities for light-matter coupling and surface-enhanced sensing. Recently, all-dielectric metasurfaces with ultrashar
Externí odkaz:
http://arxiv.org/abs/2308.15644