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of 52
pro vyhledávání: '"Wu, Jiqing"'
Due to the heterogeneity of real-world data, the widely accepted independent and identically distributed (IID) assumption has been criticized in recent studies on causality. In this paper, we argue that instead of being a questionable assumption, IID
Externí odkaz:
http://arxiv.org/abs/2203.00332
Autor:
Wu, Jiqing, Koelzer, Viktor H.
Publikováno v:
In Computers in Biology and Medicine September 2024 179
Autor:
Wu, Jiqing, Horeweg, Nanda, de Bruyn, Marco, Nout, Remi A., Jürgenliemk-Schulz, Ina M., Lutgens, Ludy C. H. W., Jobsen, Jan J., van der Steen-Banasik, Elzbieta M., Nijman, Hans W., Smit, Vincent T. H. B. M., Bosse, Tjalling, Creutzberg, Carien L., Koelzer, Viktor H.
Randomized controlled trials (RCTs) are considered as the gold standard for testing causal hypotheses in the clinical domain. However, the investigation of prognostic variables of patient outcome in a hypothesized cause-effect route is not feasible u
Externí odkaz:
http://arxiv.org/abs/2201.05773
Autor:
Wu, Jiqing, Koelzer, Viktor H.
Publikováno v:
In Computational and Structural Biotechnology Journal December 2024 23:3481-3488
Autor:
Wakkerman, Famke C, Wu, Jiqing, Putter, Hein, Jürgenliemk-Schulz, Ina M, Jobsen, Jan J, Lutgens, Ludy C H W, Haverkort, Marie A D, de Jong, Marianne A, Mens, Jan Willem M, Wortman, Bastiaan G, Nout, Remi A, Léon-Castillo, Alicia, Powell, Melanie E, Mileshkin, Linda R, Katsaros, Dionyssios, Alfieri, Joanne, Leary, Alexandra, Singh, Naveena, de Boer, Stephanie M, Nijman, Hans W, Smit, Vincent T H B M, Bosse, Tjalling, Koelzer, Viktor H, Creutzberg, Carien L, Horeweg, Nanda *
Publikováno v:
In The Lancet Oncology June 2024 25(6):779-789
This paper introduces a divide-and-conquer inspired adversarial learning (DACAL) approach for photo enhancement. The key idea is to decompose the photo enhancement process into hierarchically multiple sub-problems, which can be better conquered from
Externí odkaz:
http://arxiv.org/abs/1910.10455
Autor:
Wu, Jiqing, Huang, Zhiwu, Acharya, Dinesh, Li, Wen, Thoma, Janine, Paudel, Danda Pani, Van Gool, Luc
In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions. Unfortunately, it is challenging to approximate the WD of high-dimensional distributions. I
Externí odkaz:
http://arxiv.org/abs/1904.05408
Autor:
Chen, Hanxiang, Hou, Shuting, Cui, Haoyuan, Wang, Chao, Zhang, Ming, Li, Hongping, Xu, Hui, Wu, Jiqing, Zhu, Wenshuai
Publikováno v:
In Journal of Molecular Liquids 1 June 2023 379
Generative modeling over natural images is one of the most fundamental machine learning problems. However, few modern generative models, including Wasserstein Generative Adversarial Nets (WGANs), are studied on manifold-valued images that are frequen
Externí odkaz:
http://arxiv.org/abs/1712.01551
This paper presents a new problem of unpaired face translation between images and videos, which can be applied to facial video prediction and enhancement. In this problem there exist two major technical challenges: 1) designing a robust translation m
Externí odkaz:
http://arxiv.org/abs/1712.00971