Results 121 to 130 of about 22,384 (303)
Co-occurrence probabilities between mosquito vectors of West Nile and Eastern equine encephalitis viruses using Markov Random Fields (MRFcov). [PDF]
Parasit Vectors, 2023 Sallam MF +10 more
europepmc +1 more source
Combinatorial Markov Random Fields [PDF]
, 2008 . A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatorial Markov random fields (Comrafs), which are Markov random fields where some of the
Ron Bekkerman +2 more
core
Business Strategy and the Environment, EarlyView.ABSTRACT The concept of predictive maintenance in advanced manufacturing systems is crucial from the point of view of resource efficiency in the era of high competitiveness forced by energy transformation in the digital economy. Against the backdrop of sustainability and the opportunities a data cooperative offers, the combination of predictive ...
Christian Schachtner +6 more
wiley +1 more source
Gene regulatory networks from multifactorial perturbations using graphical lasso: Application to the DREAM4 challenge [PDF]
, 2010 A major challenge in the field of systems biology consists of predicting gene regulatory networks based on different training data. Within the DREAM4 initiative, we took part in the multifactorial sub-challenge that aimed to predict gene regulatory ...
ter Braak, C.J.F. +17 more
core +1 more source
ESG Controversies in Global Firms: A Black Mark?
Business Strategy and the Environment, EarlyView.ABSTRACT Despite increasing attention paid by companies to sustainability, there is still evidence of environmental, social and governance (commonly referred to as ESG) scandals. As research on this topic is scant, this paper aims to analyse the impact of ESG controversies on firms' sustainability practices, that is, ESG policies, as well as ...
Beatrice Bais, Guido Orzes, Marco Sartor
wiley +1 more source
Remote Sensing, 2017 Change detection has been widely used in remote sensing, such as for disaster assessment and urban expansion detection. Although it is convenient to use unsupervised methods to detect changes from multi-temporal images, the results could be further ...
Huai Yu +4 more
doaj +1 more source
Image Labeling with Markov Random Fields and Conditional Random Fields
CoRR, 2018 Most existing methods for object segmentation in computer vision are formulated as a labeling task. This, in general, could be transferred to a pixel-wise label assignment task, which is quite similar to the structure of hidden Markov random field. In terms of Markov random field, each pixel can be regarded as a state and has a transition probability ...
Shangxuan Wu, Xinshuo Weng
openaire +2 more sources
Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions
Canadian Journal of Statistics, EarlyView.Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni +2 more
wiley +1 more source
Sampling Strategies for Fast Updating of Gaussian Markov Random Fields. [PDF]
Am Stat, 2021 Brown DA, McMahan CS, Self SW.
europepmc +1 more source
Power spectral density and the brain
Canadian Journal of Statistics, EarlyView.Abstract Time series from M/EEG (magneto/electroencephalography) and ECoG (electrocorticography) recordings are common sources of information about brain function. The power spectral density (PSD) preserves much of this information, up to second order. In the current decade, a burst of brain diagnostics using the slope of log(PSD) has appeared.
Priscilla E. Greenwood +2 more
wiley +1 more source