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Related papers: G1-Renewal Process as Repairable System Model

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Generative models such as denoising diffusion models are quickly advancing their ability to approximate highly complex data distributions. They are also increasingly leveraged in scientific machine learning, where samples from the implied…

Machine Learning · Computer Science 2025-03-14 Jan-Hendrik Bastek , WaiChing Sun , Dennis M. Kochmann

Doubly intractable distributions arise in many settings, for example in Markov models for point processes and exponential random graph models for networks. Bayesian inference for these models is challenging because they involve intractable…

Computation · Statistics 2019-04-03 Jaewoo Park , Murali Haran

Most existing MRI reconstruction methods perform tar-geted reconstruction of the entire MR image without tak-ing specific tissue regions into consideration. This may fail to emphasize the reconstruction accuracy on im-portant tissues for…

Image and Video Processing · Electrical Eng. & Systems 2023-09-06 Yu Guan , Chuanming Yu , Shiyu Lu , Zhuoxu Cui , Dong Liang , Qiegen Liu

The reliability of processes with moving elastic and isotropic material containing initial cracks is considered in terms of fracture. The material is modelled as a moving plate which is simply supported from two of its sides and subjected…

Computational Engineering, Finance, and Science · Computer Science 2016-04-25 Maria Tirronen

Time series prediction is often complicated by distribution shift which demands adaptive models to accommodate time-varying distributions. We frame time series prediction under distribution shift as a weighted empirical risk minimisation…

Machine Learning · Computer Science 2022-07-26 Stefanos Bennett , Jase Clarkson

The predictability problem for systems with different characteristic time scales is investigated. It is shown that even in simple chaotic dynamical systems, the leading Lyapunov exponent is not sufficient to estimate the predictability…

chao-dyn · Physics 2009-10-31 G. Boffetta , P. Giuliani , G. Paladin , A. Vulpiani

This paper discusses the problem of adaptive estimation of a univariate object like the value of a regression function at a given point or a linear functional in a linear inverse problem. We consider an adaptive procedure originated from…

Statistics Theory · Mathematics 2009-08-26 Vladimir Spokoiny , Céline Vial

This paper compares two imperfect repair models for a degrading system, with deterioration level modeled by a non homogeneous gamma process. Both models consider instantaneous and periodic repairs. The first model assumes that a repair…

Optimization and Control · Mathematics 2024-01-24 Sophie Mercier , Inma T. Castro

The performance of graph neural networks (GNNs) is susceptible to discrepancies between training and testing sample distributions. Prior studies have attempted to mitigating the impact of distribution shift by reconstructing node features…

Machine Learning · Computer Science 2025-04-18 Jielong Yang , Rui Ding , Feng Ji , Hongbin Wang , Linbo Xie

To recover simultaneous multiple failures in erasure coded storage systems, Patrick Lee et al introduce concurrent repair based minimal storage regenerating codes to reduce repair traffic. The architecture of this approach is simpler and…

Information Theory · Computer Science 2016-04-25 Huayu Zhang , Hui Li , Hanxu Hou , K. W. Shum , ShuoYen Robert Li

A new algorithm is developed to tackle the issue of sampling non-Gaussian model parameter posterior probability distributions that arise from solutions to Bayesian inverse problems. The algorithm aims to mitigate some of the hurdles faced…

Machine Learning · Statistics 2019-11-19 Leen Alawieh , Jonathan Goodman , John B. Bell

In this paper, we proposed a new lifetime distribution namely generalized weighted Lindley (GLW) distribution. The GLW distribution is a useful generalization of the weighted Lindley distribution, which accommodates increasing, decreasing,…

Statistics Theory · Mathematics 2016-07-20 P. L. Ramos , F. Louzada

Research on the distribution of prime numbers has revealed a dual character: deterministic in definition yet exhibiting statistical behavior reminiscent of random processes. In this paper we show that it is possible to use an image-focused…

The number of end devices that use the last mile wireless connectivity is dramatically increasing with the rise of smart infrastructures and require reliable functioning to support smooth and efficient business processes. To efficiently…

Machine Learning · Computer Science 2022-02-21 Blaž Bertalanič , Marko Meža , Carolina Fortuna

Real-life parallel machine scheduling problems can be characterized by: (i) limited information about the exact task duration at scheduling time, and (ii) an opportunity to reschedule the remaining tasks each time a task processing is…

Optimization and Control · Mathematics 2023-11-22 Izack Cohen , Krzysztof Postek , Shimrit Shtern

We use point processes theory to describe the asymptotic distribution of all upper order statistics for observations collected at renewal times. As a corollary, we obtain limiting theorems for corresponding extremal processes.

Probability · Mathematics 2016-08-08 Bojan Basrak , Drago Špoljarić

Phase retrieval is a nonlinear inverse problem that arises in a wide range of imaging modalities, from electron microscopy to Fourier ptychography. In particular, the reconstruction is facilitated when the sensing matrix is i.i.d. random,…

The theory of ``Markov-up'' processes is being developed. This is a new class of stochastic processes with ``partial'' markovian features; it could also be called ``one-sided Markov''. Such a behavior may be found in the real world and in…

Probability · Mathematics 2024-07-01 D. O. Kalikaeva

Several real-world and abstract structures and systems are characterized by marked hierarchy to the point of being expressed as trees. Because the study of these entities often involves sampling (or discovering) the tree nodes in a specific…

Physics and Society · Physics 2022-04-18 Alexandre Benatti , Luciano da F. Costa

The flux reconstruction (FR) approach offers a flexible framework for describing a range of high-order numerical schemes; including nodal discontinuous Galerkin and spectral difference schemes. This is accomplished through the use of…

Numerical Analysis · Mathematics 2020-06-25 Will Trojak , Freddie Witherden
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