Zobrazeno 1 - 10
of 67 970
pro vyhledávání: '"P. Can"'
Publikováno v:
BMC Veterinary Research, Vol 19, Iss 1, Pp 1-13 (2023)
Abstract Background Intervertebral disc herniation (IVDH) is one of the most common causes of spinal cord injury (SCI) in dogs. As a result of acute SCI, a complex inflammatory response occurs in the spinal cord. Th17 cells (Th17) produce pro-inflamm
Externí odkaz:
https://doaj.org/article/8028c619dea945968d50b18aea18ac3a
Outperforming autoregressive models on categorical data distributions, such as textual data, remains challenging for continuous diffusion and flow models. Discrete flow matching, a recent framework for modeling categorical data, has shown competitive
Externí odkaz:
http://arxiv.org/abs/2411.00759
Neural contextual biasing allows speech recognition models to leverage contextually relevant information, leading to improved transcription accuracy. However, the biasing mechanism is typically based on a cross-attention module between the audio and
Externí odkaz:
http://arxiv.org/abs/2411.00664
Autor:
Yang, Weiqin, Chen, Jiawei, Xin, Xin, Zhou, Sheng, Hu, Binbin, Feng, Yan, Chen, Chun, Wang, Can
Softmax Loss (SL) is widely applied in recommender systems (RS) and has demonstrated effectiveness. This work analyzes SL from a pairwise perspective, revealing two significant limitations: 1) the relationship between SL and conventional ranking metr
Externí odkaz:
http://arxiv.org/abs/2411.00163
Autor:
Guo, Junlin, Lu, Siqi, Cui, Can, Deng, Ruining, Yao, Tianyuan, Tao, Zhewen, Lin, Yizhe, Lionts, Marilyn, Liu, Quan, Xiong, Juming, Wang, Yu, Zhao, Shilin, Chang, Catie, Wilkes, Mitchell, Yin, Mengmeng, Yang, Haichun, Huo, Yuankai
Training AI foundation models has emerged as a promising large-scale learning approach for addressing real-world healthcare challenges, including digital pathology. While many of these models have been developed for tasks like disease diagnosis and t
Externí odkaz:
http://arxiv.org/abs/2411.00078
Autor:
Mollaali, Amirhossein, Zufferey, Gabriel, Constante-Flores, Gonzalo, Moya, Christian, Li, Can, Lin, Guang, Yue, Meng
This paper proposes a new data-driven methodology for predicting intervals of post-fault voltage trajectories in power systems. We begin by introducing the Quantile Attention-Fourier Deep Operator Network (QAF-DeepONet), designed to capture the compl
Externí odkaz:
http://arxiv.org/abs/2410.24162
Distant-microphone meeting transcription is a challenging task. State-of-the-art end-to-end speaker-attributed automatic speech recognition (SA-ASR) architectures lack a multichannel noise and reverberation reduction front-end, which limits their per
Externí odkaz:
http://arxiv.org/abs/2410.21849
Autor:
Chen, Can, Wang, Jun-Kun
Developing algorithms to differentiate between machine-generated texts and human-written texts has garnered substantial attention in recent years. Existing methods in this direction typically concern an offline setting where a dataset containing a mi
Externí odkaz:
http://arxiv.org/abs/2410.22318
Autor:
Can, Mahir Bilen
Poset metrics in the context of stabilizer codes are investigated. MDS stabilizer poset codes are defined. Various characterizations of these quantum codes are found. Methods for producing examples are proposed.
Externí odkaz:
http://arxiv.org/abs/2410.20993
A wide variety of data can be represented using third-order tensors, spanning applications in chemometrics, psychometrics, and image processing. However, traditional data-driven frameworks are not naturally equipped to process tensors without first u
Externí odkaz:
http://arxiv.org/abs/2410.20541