Gaussian Entanglement Distribution via Satellite [PDF]
Physical Review A, 2015 In this work we analyse three quantum communication schemes for the generation of Gaussian entanglement between two ground stations. Communication occurs via a satellite over two independent atmospheric fading channels dominated by turbulence-induced ...
Hosseinidehaj, Nedasadat +1 more
core +4 more sources
Conditional Gaussian Distribution Learning for Open Set Recognition [PDF]
Computer Vision and Pattern Recognition, 2020 Deep neural networks have achieved state-of-the-art performance in a wide range of recognition/classification tasks. However, when applying deep learning to real-world applications, there are still multiple challenges. A typical challenge is that unknown
Xin Sun +4 more
semanticscholar +1 more source
IEEE Transactions on Sustainable Energy, 2022 Accordingto recent grid codes, large-scale wind turbines (WTs) are required to provide fast frequency response (FFR). The existing stepwise inertial control methods suggest immediate incremental power injection by WTs, followed by the abrupt over ...
M. Kheshti +5 more
semanticscholar +1 more source
Quantum anomaly detection with density estimation and multivariate Gaussian distribution [PDF]
Physical Review A, 2019 We study quantum anomaly detection with density estimation and multivariate Gaussian distribution. Both algorithms are constructed using the standard gate-based model of quantum computing.
Jin‐Min Liang +3 more
semanticscholar +1 more source
statmod: Probability Calculations for the Inverse Gaussian Distribution [PDF]
The R Journal, 2016 The inverse Gaussian distribution (IGD) is a well known and often used probability distribution for which fully reliable numerical algorithms have not been available.
Göknur Giner, G. Smyth
semanticscholar +1 more source
Subdifferential characterization of probability functions under Gaussian distribution [PDF]
Mathematical programming, 2017 Probability functions figure prominently in optimization problems of engineering. They may be nonsmooth even if all input data are smooth. This fact motivates the consideration of subdifferentials for such typically just continuous functions.
A. Hantoute, R. Henrion, P. Pérez-Aros
semanticscholar +1 more source
Self-adaptation of mutation distribution in evolutionary algorithms [PDF]
, 2007 This paper is posted here with permission from IEEE - Copyright @ 2007 IEEEThis paper proposes a self-adaptation method to control not only the mutation strength parameter, but also the mutation distribution for evolutionary algorithms. For this purpose,
Tinos, R, Yang, S
core +2 more sources
Higher order moments of the density field in a parameterized sequence of non-gaussian theories [PDF]
, 1998 We calculate the higher order moments in a sequence of models where the initial density fluctuations are drawn from a chi^2_nu distribution with a power-law power spectrum.
Antoniadis +44 more
core +2 more sources
PixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction [PDF]
Computer Vision and Pattern Recognition, 2023 We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time and memory-efficient rendering for scalable training as well as fast 3D
David Charatan +3 more
semanticscholar +1 more source
Applying Gaussian distributed constraints to Gaussian distributed variables [PDF]
Information Fusion, 2016 34 pages, 12 figures, accepted to Information Fusion. Updated to fix minor errors in equations (33), (34), and (B.12)
Andrew W. Palmer +2 more
openaire +2 more sources