Zobrazeno 1 - 10
of 60 238
pro vyhledávání: '"WANG CHAO"'
While consumer displays increasingly support more than 10 stops of dynamic range, most image assets such as internet photographs and generative AI content remain limited to 8-bit low dynamic range (LDR), constraining their utility across high dynamic
Externí odkaz:
http://arxiv.org/abs/2412.14456
We propose a method for conducting algebraic program analysis (APA) incrementally in response to changes of the program under analysis. APA is a program analysis paradigm that consists of two distinct steps: computing a path expression that succinctl
Externí odkaz:
http://arxiv.org/abs/2412.10632
In this paper, we study the asymptotic behavior of the solution of the Navier-Stokes equations in the half plane at high Reynolds number regime, when the initial vorticity belongs to the Yudovich class and is supported away from the boundary. We prov
Externí odkaz:
http://arxiv.org/abs/2412.03198
Realised volatility has become increasingly prominent in volatility forecasting due to its ability to capture intraday price fluctuations. With a growing variety of realised volatility estimators, each with unique advantages and limitations, selectin
Externí odkaz:
http://arxiv.org/abs/2411.17136
Graph neural architecture search (GNAS) can customize high-performance graph neural network architectures for specific graph tasks or datasets. However, existing GNAS methods begin searching for architectures from a zero-knowledge state, ignoring the
Externí odkaz:
http://arxiv.org/abs/2411.17339
Autor:
Zhang, Gong, Primaatmaja, Ignatius William, Chen, Yue, Ng, Si Qi, Ng, Hong Jie, Pistoia, Marco, Gong, Xiao, Goh, Koon Tong, Wang, Chao, Lim, Charles
The power of quantum random number generation is more than just the ability to create truly random numbers$\unicode{x2013}$it can also enable self-testing, which allows the user to verify the implementation integrity of certain critical quantum compo
Externí odkaz:
http://arxiv.org/abs/2411.13712
Recently, implicit neural representations (INRs) have attracted increasing attention for multi-dimensional data recovery. However, INRs simply map coordinates via a multi-layer perception (MLP) to corresponding values, ignoring the inherent semantic
Externí odkaz:
http://arxiv.org/abs/2411.11356
The observed jet precession period of approximately 11 years for M87* strongly suggests the presence of a supermassive rotating black hole with a tilted accretion disk at the center of the galaxy. By modeling the motion of the tilted accretion disk p
Externí odkaz:
http://arxiv.org/abs/2411.07481
Solving partial differential equations (PDEs) is essential in scientific forecasting and fluid dynamics. Traditional approaches often incur expensive computational costs and trade-offs in efficiency and accuracy. Recent deep neural networks improve a
Externí odkaz:
http://arxiv.org/abs/2411.04516