Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Tran, Alasdair"'
Autor:
Nguyen, Tuan Dung, Chen, Ziyu, Carroll, Nicholas George, Tran, Alasdair, Klein, Colin, Xie, Lexing
The ever-growing textual records of contemporary social issues, often discussed online with moral rhetoric, present both an opportunity and a challenge for studying how moral concerns are debated in real life. Moral foundations theory is a taxonomy o
Externí odkaz:
http://arxiv.org/abs/2311.10219
Autor:
Nguyen, Tuan Dung, Lyall, Georgiana, Tran, Alasdair, Shin, Minjeong, Carroll, Nicholas George, Klein, Colin, Xie, Lexing
Moral dilemmas play an important role in theorizing both about ethical norms and moral psychology. Yet thought experiments borrowed from the philosophical literature often lack the nuances and complexity of real life. We leverage 100,000 threads -- t
Externí odkaz:
http://arxiv.org/abs/2203.16762
We propose the Factorized Fourier Neural Operator (F-FNO), a learning-based approach for simulating partial differential equations (PDEs). Starting from a recently proposed Fourier representation of flow fields, the F-FNO bridges the performance gap
Externí odkaz:
http://arxiv.org/abs/2111.13802
Publikováno v:
Proceedings of The Web Conference 2021 (WWW '21)
We propose a new model for networks of time series that influence each other. Graph structures among time series are found in diverse domains, such as web traffic influenced by hyperlinks, product sales influenced by recommendation, or urban transpor
Externí odkaz:
http://arxiv.org/abs/2102.07289
Autor:
Shin, Minjeong, Tran, Alasdair, Wu, Siqi, Mathews, Alexander, Wang, Rong, Lyall, Georgiana, Xie, Lexing
Publikováno v:
The Proceedings of the Fourteenth ACM International Conference on Web Search and Data Mining (WSDM), 2021
The collective attention on online items such as web pages, search terms, and videos reflects trends that are of social, cultural, and economic interest. Moreover, attention trends of different items exhibit mutual influence via mechanisms such as hy
Externí odkaz:
http://arxiv.org/abs/2102.01974
Publikováno v:
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 13035-13045
We propose an end-to-end model which generates captions for images embedded in news articles. News images present two key challenges: they rely on real-world knowledge, especially about named entities; and they typically have linguistically rich capt
Externí odkaz:
http://arxiv.org/abs/2004.08070
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