Zobrazeno 1 - 10
of 9 002
pro vyhledávání: '"Weide A"'
The paper "Sorting with Bialgebras and Distributive Laws" by Hinze et al. uses the framework of bialgebraic semantics to define sorting algorithms. From distributive laws between functors they construct pairs of sorting algorithms using both folds an
Externí odkaz:
http://arxiv.org/abs/2412.08362
Autor:
Goy, Matthias, Krause, Jan, Bayraktar, Ömer, Ancsin, Philippe, David, Florian, Dirmeier, Thomas, Doell, Nico, Dwan, Jansen, Fohlmeister, Friederike, Freund, Ronald, Goebel, Thorsten A., Hilt, Jonas, Jaksch, Kevin, Kohout, Oskar, Kopf, Teresa, Krzic, Andrej, Leipe, Markus, Leuchs, Gerd, Marquardt, Christoph, Mendez, Karen L., Milde, Anja, Mishra, Sarika, Moll, Florian, Paciorek, Karolina, Pavlovic, Natasa, Richter, Stefan, Rothe, Markus, Rüddenklau, René, Sauer, Gregor, Schell, Martin, Schreck, Jan, Schreier, Andy, Sharma, Sakshi, Spier, Simon, Spiess, Christopher, Steinlechner, Fabian, Tünnermann, Andreas, Vural, Hüseyin, Walenta, Nino, Weide, Stefan
This paper presents the development and implementation of a versatile ad-hoc metropolitan-range Quantum Key Distribution (QKD) network. The approach presented integrates various types of physical channels and QKD protocols, and a mix of trusted and u
Externí odkaz:
http://arxiv.org/abs/2412.07473
Autor:
van der Weide, Niels
Internal language theorems are fundamental in categorical logic, since they express an equivalence between syntax and semantics. One of such theorems was proven by Clairambault and Dybjer, who corrected the result originally by Seely. More specifical
Externí odkaz:
http://arxiv.org/abs/2411.06636
Diffusion-weighted magnetic resonance imaging (dMRI) is the only non-invasive tool for studying white matter tracts and structural connectivity of the brain. These assessments rely heavily on tractography techniques, which reconstruct virtual streaml
Externí odkaz:
http://arxiv.org/abs/2408.14326
In this paper, we introduce a novel Gaussian mixture based evidential learning solution for robust stereo matching. Diverging from previous evidential deep learning approaches that rely on a single Gaussian distribution, our framework posits that ind
Externí odkaz:
http://arxiv.org/abs/2408.02796
We present a deep neural network-enabled method to accelerate near-field (NF) antenna measurement. We develop a Near-field Super-resolution Network (NFS-Net) to reconstruct significantly undersampled near-field data as high-resolution data, which con
Externí odkaz:
http://arxiv.org/abs/2406.17244
Autor:
Li, Fulan, Guo, Yunfei, Xu, Wenda, Zhang, Weide, Zhao, Fangyun, Wang, Baiyu, Du, Huaguang, Zhang, Chengkun
Publikováno v:
Frontiers in Rehabilitation Sciences, 5 (2024)
This paper presents GARD, an upper limb end-effector rehabilitation device developed for stroke patients. GARD offers assistance force along or towards a 2D trajectory during physical therapy sessions. GARD employs a non-backdrivable mechanism with n
Externí odkaz:
http://arxiv.org/abs/2406.14795
Autor:
Liu, Weide, Hou, Jingwen, Zhong, Xiaoyang, Zhan, Huijing, Cheng, Jun, Fang, Yuming, Yue, Guanghui
Deep learning-based brain tumor segmentation (BTS) models for multi-modal MRI images have seen significant advancements in recent years. However, a common problem in practice is the unavailability of some modalities due to varying scanning protocols
Externí odkaz:
http://arxiv.org/abs/2406.10175
Protein-protein interactions (PPIs) play key roles in a broad range of biological processes. Numerous strategies have been proposed for predicting PPIs, and among them, graph-based methods have demonstrated promising outcomes owing to the inherent gr
Externí odkaz:
http://arxiv.org/abs/2404.10450
The interest in predicting online learning performance using ML algorithms has been steadily increasing. We first conducted a scientometric analysis to provide a systematic review of research in this area. The findings show that most existing studies
Externí odkaz:
http://arxiv.org/abs/2406.11847