Zobrazeno 1 - 10
of 5 019
pro vyhledávání: '"Nguyen, Thu A."'
Autor:
Nguyen, Trung-Hieu, Vuong, Truong-Giang, Duong, Hong-Nam, Nguyen, Son, Vo, Hieu Dinh, Aoki, Toshiaki, Nguyen, Thu-Trang
Autonomous vehicles (AVs) have demonstrated significant potential in revolutionizing transportation, yet ensuring their safety and reliability remains a critical challenge, especially when exposed to dynamic and unpredictable environments. Real-world
Externí odkaz:
http://arxiv.org/abs/2412.02574
We compute the regularity of powers and symbolic powers of edge ideals of all cubic circulant graphs. In particular, we establish Conjecture of Minh for cubic circulant graphs.
Externí odkaz:
http://arxiv.org/abs/2409.20161
Autor:
Bui, Tuan-Dung, Luu-Van, Duc-Thieu, Nguyen, Thanh-Phat, Nguyen, Thu-Trang, Nguyen, Son, Vo, Hieu Dinh
Code completion is essential in software development, helping developers by predicting code snippets based on context. Among completion tasks, Method Body Completion (MBC) is particularly challenging as it involves generating complete method bodies b
Externí odkaz:
http://arxiv.org/abs/2409.15204
Autor:
Dung, Nguyen Tien, Hang, Nguyen Thu
In this paper, we first establish general bounds on the Fisher information distance to the class of normal distributions of Malliavin differentiable random variables. We then study the rate of Fisher information convergence in the central limit theor
Externí odkaz:
http://arxiv.org/abs/2408.09797
Publikováno v:
Physica B: Condensed Matter 2024
In this study, based on the quantum kinetic equation approach, we systematically present the radio-electric effect in asymmetric semi-parabolic quantum wells under the influence of a laser radiation field taking into account the electron-longitudinal
Externí odkaz:
http://arxiv.org/abs/2407.09938
Large Language Models for Code (code LLMs) have demonstrated remarkable performance across various software engineering (SE) tasks, increasing the application of code LLMs in software development. Despite the success of code LLMs, there remain signif
Externí odkaz:
http://arxiv.org/abs/2407.03611
As the adoption of Artificial Intelligence (AI) models expands into critical real-world applications, ensuring the explainability of these models becomes paramount, particularly in sensitive fields such as medicine and finance. Linear Discriminant An
Externí odkaz:
http://arxiv.org/abs/2407.00710
Missing data is a prevalent issue that can significantly impair model performance and interpretability. This paper briefly summarizes the development of the field of missing data with respect to Explainable Artificial Intelligence and experimentally
Externí odkaz:
http://arxiv.org/abs/2407.00411
We investigate matrix-weighted bounds for the sublinear non-kernel operators considered by F. Bernicot, D. Frey, and S. Petermichl. We extend their result to sublinear operators acting upon vector-valued functions. First, we dominate these operators
Externí odkaz:
http://arxiv.org/abs/2404.02246
Despite its technological breakthroughs, eXplainable Artificial Intelligence (XAI) research has limited success in producing the {\em effective explanations} needed by users. In order to improve XAI systems' usability, practical interpretability, and
Externí odkaz:
http://arxiv.org/abs/2403.14496