Zobrazeno 1 - 10
of 30 813
pro vyhledávání: '"Yuliang An"'
Publikováno v:
Biotechnology for Biofuels and Bioproducts, Vol 17, Iss 1, Pp 1-9 (2024)
Abstract Oleaginous green microalgae are often mentioned in algae-based biodiesel industry, but most of them belong to specific genus (Chlorella, Scenedesmus, Botryococcus and Desmodesmus). Thus, the microalgal germplasm resources for biodiesel produ
Externí odkaz:
https://doaj.org/article/debf14d83bbd489b9ca391fef7f03c33
Time-series foundation models have the ability to run inference, mainly forecasting, on any type of time series data, thanks to the informative representations comprising waveform features. Wearable sensing data, on the other hand, contain more varia
Externí odkaz:
http://arxiv.org/abs/2412.09758
Given that visual foundation models (VFMs) are trained on extensive datasets but often limited to 2D images, a natural question arises: how well do they understand the 3D world? With the differences in architecture and training protocols (i.e., objec
Externí odkaz:
http://arxiv.org/abs/2412.09606
Autor:
Dang, Yizhou, Zhang, Jiahui, Liu, Yuting, Yang, Enneng, Liang, Yuliang, Guo, Guibing, Zhao, Jianzhe, Wang, Xingwei
By generating new yet effective data, data augmentation has become a promising method to mitigate the data sparsity problem in sequential recommendation. Existing works focus on augmenting the original data but rarely explore the issue of imbalanced
Externí odkaz:
http://arxiv.org/abs/2412.08300
Autor:
Liu, Jian-Guo, Wang, Yuliang
In many real-world scenarios, the underlying random fluctuations are non-Gaussian, particularly in contexts where heavy-tailed data distributions arise. A typical example of such non-Gaussian phenomena calls for L\'evy noise, which accommodates jumps
Externí odkaz:
http://arxiv.org/abs/2412.06291
Autor:
Wu, Junfeng, Jiang, Yi, Ma, Chuofan, Liu, Yuliang, Zhao, Hengshuang, Yuan, Zehuan, Bai, Song, Bai, Xiang
We present Liquid, an auto-regressive generation paradigm that seamlessly integrates visual comprehension and generation by tokenizing images into discrete codes and learning these code embeddings alongside text tokens within a shared feature space f
Externí odkaz:
http://arxiv.org/abs/2412.04332
With increasing numbers of vulnerabilities exposed on the internet, autonomous penetration testing (pentesting) has emerged as an emerging research area, while reinforcement learning (RL) is a natural fit for studying autonomous pentesting. Previous
Externí odkaz:
http://arxiv.org/abs/2412.04078
Autor:
Tailiang, Liu, Yuliang, Shen
In this paper, we introduce a class of vanishing Carleson measures with conformal invariance and corresponding strongly vanishing symmetric homeomorphisms on the real line and prove that they can be mutually generated under quasiconformal mappings. T
Externí odkaz:
http://arxiv.org/abs/2411.16042
Autor:
Li, Haotian, Zhang, Rui, Wang, Lingzhi, Yu, Bin, Wang, Youwei, Wei, Yuliang, Wang, Kai, Da Xu, Richard Yi, Wang, Bailing
Recent progress in knowledge graph completion (KGC) has focused on text-based approaches to address the challenges of large-scale knowledge graphs (KGs). Despite their achievements, these methods often overlook the intricate interconnections between
Externí odkaz:
http://arxiv.org/abs/2411.15694
Autor:
Liang, Yuliang, Liu, Yuting, Dang, Yizhou, Yang, Enneng, Guo, Guibing, Cai, Wei, Zhao, Jianzhe, Wang, Xingwei
Medication recommender is to suggest appropriate medication combinations based on a patient's health history, e.g., diagnoses and procedures. Existing works represent different diagnoses/procedures well separated by one-hot encodings. However, they i
Externí odkaz:
http://arxiv.org/abs/2411.03143