Zobrazeno 1 - 10
of 5 134
pro vyhledávání: '"DONG, Bo"'
Graph Neural Networks (GNNs) have been widely employed for semi-supervised node classification tasks on graphs. However, the performance of GNNs is significantly affected by label noise, that is, a small amount of incorrectly labeled nodes can substa
Externí odkaz:
http://arxiv.org/abs/2411.11020
Autor:
Shao, Zhijing, Wang, Duotun, Tian, Qing-Yao, Yang, Yao-Dong, Meng, Hengyu, Cai, Zeyu, Dong, Bo, Zhang, Yu, Zhang, Kang, Wang, Zeyu
Although neural rendering has made significant advancements in creating lifelike, animatable full-body and head avatars, incorporating detailed expressions into full-body avatars remains largely unexplored. We present DEGAS, the first 3D Gaussian Spl
Externí odkaz:
http://arxiv.org/abs/2408.10588
Autor:
Lou, Yan-Chao, Ren, Zhi-Cheng, Chen, Chao, Wan, Pei, Zhu, Wen-Zheng, Wang, Jing, Xue, Shu-Tian, Dong, Bo-Wen, Ding, Jianping, Wang, Xi-Lin, Wang, Hui-Tian
Publikováno v:
Phys. Rev. Applied 22, 014052 (2024)
Recently, great progress has been made in the entanglement of multiple photons at various wavelengths and in different degrees of freedom for optical quantum information applied in diverse scenarios. However, multi-photon entanglement in the transmis
Externí odkaz:
http://arxiv.org/abs/2407.16983
Autor:
Wang, Yang, Mei, Haiyang, Bao, Qirui, Wei, Ziqi, Shou, Mike Zheng, Li, Haizhou, Dong, Bo, Yang, Xin
We introduce a novel multimodality synergistic knowledge distillation scheme tailored for efficient single-eye motion recognition tasks. This method allows a lightweight, unimodal student spiking neural network (SNN) to extract rich knowledge from an
Externí odkaz:
http://arxiv.org/abs/2407.09521
In noisy label learning, estimating noisy class posteriors plays a fundamental role for developing consistent classifiers, as it forms the basis for estimating clean class posteriors and the transition matrix. Existing methods typically learn noisy c
Externí odkaz:
http://arxiv.org/abs/2405.05714
In recent years, with the rapid development of graph neural networks (GNN), more and more graph datasets have been published for GNN tasks. However, when an upstream data owner publishes graph data, there are often many privacy concerns, because many
Externí odkaz:
http://arxiv.org/abs/2403.00030
Homography Initialization and Dynamic Weighting Algorithm Based on a Downward-Looking Camera and IMU
In recent years, the technology in visual-inertial odometry (VIO) has matured considerably and has been widely used in many applications. However, we still encounter challenges when applying VIO to a micro air vehicle (MAV) equipped with a downward-l
Externí odkaz:
http://arxiv.org/abs/2311.09622
Autor:
Wang, Luhong, Li, Yan, Xie, Shengyi, Liu, Fuyang, Sun, Hualei, Huang, Caoxin, Gao, Yang, Nakagawa, Takeshi, Fu, Boyang, Dong, Bo, Cao, Zhenhui, Yu, Runze, Kawaguchi, Saori I., Kadobayashi, Hirokazu, Wang, Meng, Jin, Changqing, Mao, Ho-kwang, Liu, Haozhe
Very recently, a new superconductor with Tc = 80 K was reported in nickelate (La3Ni2O7) at around 15 - 40 GPa conditions (Nature, 621, 493, 2023) [1], which is the second type of unconventional superconductor, beside the cuprates, with Tc above liqui
Externí odkaz:
http://arxiv.org/abs/2311.09186
Large language models (LLMs) have demonstrated remarkable performance and tremendous potential across a wide range of tasks. However, deploying these models has been challenging due to the astronomical amount of model parameters, which requires a dem
Externí odkaz:
http://arxiv.org/abs/2311.00502
Deep Neural Networks (DNNs) are widely used for computer vision tasks. However, it has been shown that deep models are vulnerable to adversarial attacks, i.e., their performances drop when imperceptible perturbations are made to the original inputs,
Externí odkaz:
http://arxiv.org/abs/2310.06468