Zobrazeno 61 - 70
of 422
pro vyhledávání: '"Yang, Guang"'
Autor:
Fang, Yingying, Wu, Shuang, Zhang, Sheng, Huang, Chaoyan, Zeng, Tieyong, Xing, Xiaodan, Walsh, Simon, Yang, Guang
Effectively leveraging multimodal data such as various images, laboratory tests and clinical information is gaining traction in a variety of AI-based medical diagnosis and prognosis tasks. Most existing multi-modal techniques only focus on enhancing
Externí odkaz:
http://arxiv.org/abs/2311.01066
Autor:
Wu, Yinzhe, Huang, Jiahao, Wang, Fanwen, Ferreira, Pedro, Scott, Andrew, Nielles-Vallespin, Sonia, Yang, Guang
Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is the only in vivo method to non-invasively examine the microstructure of the human heart. Current research in DT-CMR aims to improve the understanding of how the cardiac microstructure relates to
Externí odkaz:
http://arxiv.org/abs/2310.20389
Autor:
Calvo-Ordonez, Sergio, Cheng, Chun-Wun, Huang, Jiahao, Zhang, Lipei, Yang, Guang, Schonlieb, Carola-Bibiane, Aviles-Rivero, Angelica I
Diffusion Probabilistic Models stand as a critical tool in generative modelling, enabling the generation of complex data distributions. This family of generative models yields record-breaking performance in tasks such as image synthesis, video genera
Externí odkaz:
http://arxiv.org/abs/2310.20092
Context: Pre-trained models (PTMs) have demonstrated significant potential in automatic code translation. However, the vulnerability of these models in translation tasks, particularly in terms of syntax, has not been extensively investigated. Objecti
Externí odkaz:
http://arxiv.org/abs/2310.18587
Autor:
Pandya, Viraj, Zhang, Haowen, Huertas-Company, Marc, Iyer, Kartheik G., McGrath, Elizabeth, Barro, Guillermo, Finkelstein, Steven L., Kuemmel, Martin, Hartley, William G., Ferguson, Henry C., Kartaltepe, Jeyhan S., Primack, Joel, Dekel, Avishai, Faber, Sandra M., Koo, David C., Bryan, Greg L., Somerville, Rachel S., Amorin, Ricardo O., Haro, Pablo Arrabal, Bagley, Micaela B., Bell, Eric F., Bertin, Emmanuel, Costantin, Luca, Dave, Romeel, Dickinson, Mark, Feldmann, Robert, Fontana, Adriano, Gavazzi, Raphael, Giavalisco, Mauro, Grazian, Andrea, Grogin, Norman A., Guo, Yuchen, Hahn, ChangHoon, Holwerda, Benne W., Kewley, Lisa J., Kirkpatrick, Allison, Koekemoer, Anton M., Lotz, Jennifer M., Lucas, Ray A., Pentericci, Laura, Perez-Gonzalez, Pablo G., Pirzkal, Nor, Kocevski, Dale D., Papovich, Casey, Ravindranath, Swara, Rose, Caitlin, Schefer, Marc, Simons, Raymond C., Straughn, Amber N., Tacchella, Sandro, Trump, Jonathan R., de la Vega, Alexander, Wilkins, Stephen M., Wuyts, Stijn, Yang, Guang, Yung, L. Y. Aaron
The 3D geometry of high-redshift galaxies remains poorly understood. We build a differentiable Bayesian model and use Hamiltonian Monte Carlo to efficiently and robustly infer the 3D shapes of star-forming galaxies in JWST-CEERS observations with $\l
Externí odkaz:
http://arxiv.org/abs/2310.15232
Autor:
Li, Ming, Yang, Guang
Thorax disease analysis in large-scale, multi-centre, and multi-scanner settings is often limited by strict privacy policies. Federated learning (FL) offers a potential solution, while traditional parameter-based FL can be limited by issues such as h
Externí odkaz:
http://arxiv.org/abs/2310.18346
Autor:
Nan, Qiong, Sheng, Qiang, Cao, Juan, Zhu, Yongchun, Wang, Danding, Yang, Guang, Li, Jintao, Shu, Kai
Both accuracy and timeliness are key factors in detecting fake news on social media. However, most existing methods encounter an accuracy-timeliness dilemma: Content-only methods guarantee timeliness but perform moderately because of limited availabl
Externí odkaz:
http://arxiv.org/abs/2310.10429
Autor:
Ronayne, Kaila, Papovich, Casey, Yang, Guang, Shen, Lu, Dickinson, Mark, Kennicutt, Robert, Alavi, Anahita, Haro, Pablo Arrabal, Bagley, Micaela, Burgarella, Denis, Bail, Aurélien Le, Bell, Eric, Cleri, Nikko, Cole, Justin, Costantin, Luca, de la Vega, Alexander, Daddi, Emanuele, Elbaz, David, Finkelstein, Steven, Grogin, Norman, Holwerda, Benne, Kartaltepe, Jeyhan, Kirkpatrick, Allison, Koekemoer, Anton, Lucas, Ray, Magnelli, Benjamin, Mobasher, Bahram, Perez-Gonzalez, Pablo, Prichard, Laura, Rafelski, Marc, Rodighiero, Giulia, Sunnquist, Ben, Teplitz, Harry, Wang, Xin, Windhorst, Rogier, Yung, L. Y. Aaron
We test the relationship between UV-derived star formation rates (SFRs) and the 7.7 ${\mu}$m polycyclic aromatic hydrocarbon (PAH) luminosities from the integrated emission of galaxies at z ~ 0 - 2. We utilize multi-band photometry covering 0.2 - 160
Externí odkaz:
http://arxiv.org/abs/2310.07766
We propose a novel Deep Active Learning (DeepAL) model-3D Wasserstein Discriminative UNet (WD-UNet) for reducing the annotation effort of medical 3D Computed Tomography (CT) segmentation. The proposed WD-UNet learns in a semi-supervised way and accel
Externí odkaz:
http://arxiv.org/abs/2310.05638
Autor:
Yang, Guang, Cao, Bing-yang
Anisotropic thermal transport plays a key role in both theoretical study and engineering practice of heat transfer, but accurately measuring anisotropic thermal conductivity remains a significant challenge. To address this issue, we propose the three
Externí odkaz:
http://arxiv.org/abs/2310.02846