Zobrazeno 1 - 10
of 1 513
pro vyhledávání: '"Zhang, Yijie"'
Autor:
Li, Yuzhu, Pillar, Nir, Liu, Tairan, Ma, Guangdong, Qi, Yuxuan, de Haan, Kevin, Zhang, Yijie, Yang, Xilin, Correa, Adrian J., Xiao, Guangqian, Jen, Kuang-Yu, Iczkowski, Kenneth A., Wu, Yulun, Wallace, William Dean, Ozcan, Aydogan
Organ transplantation serves as the primary therapeutic strategy for end-stage organ failures. However, allograft rejection is a common complication of organ transplantation. Histological assessment is essential for the timely detection and diagnosis
Externí odkaz:
http://arxiv.org/abs/2409.05255
PAC-Bayesian analysis is a frequentist framework for incorporating prior knowledge into learning. It was inspired by Bayesian learning, which allows sequential data processing and naturally turns posteriors from one processing step into priors for th
Externí odkaz:
http://arxiv.org/abs/2405.14681
Autor:
Selcuk, Sahan Yoruc, Yang, Xilin, Bai, Bijie, Zhang, Yijie, Li, Yuzhu, Aydin, Musa, Unal, Aras Firat, Gomatam, Aditya, Guo, Zhen, Angus, Darrow Morgan, Kolodney, Goren, Atlan, Karine, Haran, Tal Keidar, Pillar, Nir, Ozcan, Aydogan
Publikováno v:
BME Frontiers (2024)
Human epidermal growth factor receptor 2 (HER2) is a critical protein in cancer cell growth that signifies the aggressiveness of breast cancer (BC) and helps predict its prognosis. Accurate assessment of immunohistochemically (IHC) stained tissue sli
Externí odkaz:
http://arxiv.org/abs/2404.00837
Autor:
Yang, Xilin, Bai, Bijie, Zhang, Yijie, Aydin, Musa, Selcuk, Sahan Yoruc, Guo, Zhen, Fishbein, Gregory A., Atlan, Karine, Wallace, William Dean, Pillar, Nir, Ozcan, Aydogan
Publikováno v:
Nature Communications (2024)
Systemic amyloidosis is a group of diseases characterized by the deposition of misfolded proteins in various organs and tissues, leading to progressive organ dysfunction and failure. Congo red stain is the gold standard chemical stain for the visuali
Externí odkaz:
http://arxiv.org/abs/2403.09100
Autor:
Eryilmaz, Merve, Goncharov, Artem, Han, Gyeo-Re, Joung, Hyou-Arm, Ballard, Zachary S., Ghosh, Rajesh, Zhang, Yijie, Di Carlo, Dino, Ozcan, Aydogan
Publikováno v:
ACS Nano (2024)
The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest
Externí odkaz:
http://arxiv.org/abs/2402.17774
Recommending cold items is a long-standing challenge for collaborative filtering models because these cold items lack historical user interactions to model their collaborative features. The gap between the content of cold items and their behavior pat
Externí odkaz:
http://arxiv.org/abs/2402.09176
Autor:
Zhang, Yijie, Bei, Yuanchen, Chen, Hao, Shen, Qijie, Yuan, Zheng, Gong, Huan, Wang, Senzhang, Huang, Feiran, Huang, Xiao
Representing information of multiple behaviors in the single graph collaborative filtering (CF) vector has been a long-standing challenge. This is because different behaviors naturally form separate behavior graphs and learn separate CF embeddings. E
Externí odkaz:
http://arxiv.org/abs/2402.07659
Autor:
Ma, Guangdong, Yang, Xilin, Bai, Bijie, Li, Jingxi, Li, Yuhang, Gan, Tianyi, Shen, Che-Yung, Zhang, Yijie, Li, Yuzhu, Jarrahi, Mona, Ozcan, Aydogan
Publikováno v:
Laser & Photonics Reviews (2024)
Large-scale and high-dimensional permutation operations are important for various applications in e.g., telecommunications and encryption. Here, we demonstrate the use of all-optical diffractive computing to execute a set of high-dimensional permutat
Externí odkaz:
http://arxiv.org/abs/2402.02397
Predicting protein stability changes induced by single-point mutations has been a persistent challenge over the years, attracting immense interest from numerous researchers. The ability to precisely predict protein thermostability is pivotal for vari
Externí odkaz:
http://arxiv.org/abs/2312.04019
Graph collaborative filtering, which learns user and item representations through message propagation over the user-item interaction graph, has been shown to effectively enhance recommendation performance. However, most current graph collaborative fi
Externí odkaz:
http://arxiv.org/abs/2311.06777