Zobrazeno 1 - 10
of 55 172
pro vyhledávání: '"LIN,LI"'
This article discusses the weak pullback attractors for a damped stochastic fractional Schr\"odinger equation on $\mathbb{R}^n$ with $n\geq 2$. By utilizing the stochastic Strichartz estimates and a stopping time technique argument, the existence and
Externí odkaz:
http://arxiv.org/abs/2411.02781
The correlation between NLG automatic evaluation metrics and human evaluation is often regarded as a critical criterion for assessing the capability of an evaluation metric. However, different grouping methods and correlation coefficients result in v
Externí odkaz:
http://arxiv.org/abs/2410.16834
Autor:
Zhang, Jia, Qi, Peng, Xiao, Li, Yuan, Mengxi, Chuan, Jun, Zeng, Yaling, Lin, Li-mei, Gu, Yue, Zhang, Yan, Liao, Duan-fang, Li, Kai
Sensitive and reliable methylation assay is important for oncogentic studies and clinical applications. Here, a new methylation assay was developed by the use of adapter-dependent adapter in library preparation. This new assay avoids the use of bisul
Externí odkaz:
http://arxiv.org/abs/2410.04137
Dissipation is usually considered a negative factor for observing quantum effects and for harnessing them for quantum technologies. Here we propose a scheme for speeding up the generation of quantum entanglement between two coupled qubits by introduc
Externí odkaz:
http://arxiv.org/abs/2410.03084
Autor:
Mu-Lin, Li
In this paper, we study the deformation limit of compact Kahler manifolds. We show that the limit to be a manifold in the Fujiki class C is equivalent to the finiteness of the upper volume. We also prove the Streets-Tian conjecture for a special case
Externí odkaz:
http://arxiv.org/abs/2409.19957
Autor:
Tsai, Ting Yu, Lin, Li, Hu, Shu, Tsao, Connie W., Li, Xin, Chang, Ming-Ching, Zhu, Hongtu, Wang, Xin
Building on the success of deep learning models in cardiovascular structure segmentation, increasing attention has been focused on improving generalization and robustness, particularly in small, annotated datasets. Despite recent advancements, curren
Externí odkaz:
http://arxiv.org/abs/2409.14305
This paper presents an approach that employs log-linearization in Lie group theory and the Newton-Euler equations to derive exact linear error dynamics for a multi-rotor model, and applies this model with a novel log-linear dynamic inversion controll
Externí odkaz:
http://arxiv.org/abs/2409.10866
Few-shot imitation learning relies on only a small amount of task-specific demonstrations to efficiently adapt a policy for a given downstream tasks. Retrieval-based methods come with a promise of retrieving relevant past experiences to augment this
Externí odkaz:
http://arxiv.org/abs/2408.16944
In medical contexts, the imbalanced data distribution in long-tailed datasets, due to scarce labels for rare diseases, greatly impairs the diagnostic accuracy of deep learning models. Recent multimodal text-image supervised foundation models offer ne
Externí odkaz:
http://arxiv.org/abs/2408.14770
Autor:
Pant, Kartik A., Lin, Li-Yu, Kim, Jaehyeok, Sribunma, Worawis, Goppert, James M., Hwang, Inseok
We present a high-fidelity Mixed Reality sensor emulation framework for testing and evaluating the resilience of Unmanned Aerial Vehicles (UAVs) against false data injection (FDI) attacks. The proposed approach can be utilized to assess the impact of
Externí odkaz:
http://arxiv.org/abs/2407.09342