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The evaluation of any earthquake forecast hypothesis requires the application of rigorous statistical methods. It implies a univocal definition of the model characterising the concerned anomaly or pre...
Subject agreement and synthetic negation for the verb be show extraordinary local variation in the Survey of English Dialects (Orton et al., 1962–71). Extracting partial grammars of individuals, we co...
This paper investigates into the model-based reconstruction of complex polyhedral building roofs. A set of 3D line segments, obtained from multiview correspondence analysis of high resolution colour ...
Biomedical research has produced vast amounts of new information in the last decade but has been slow to find its use in clinical applications. Data from disparate sources such as genetic studies and ...
To be able to simulate climate change effects on forest dynamics over the whole of Switzerland, we adapted the second-generation DGVM (dynamic global vegetation model) LPJ-GUESS (Lund–Potsdam–Jena Gen...
Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models ado...
A popular approach for large scale data annotation tasks is crowdsourcing, wherein each data point is labeled by multiple noisy annotators. We consider the problem of inferring ground truth from noisy...
Inverse problems are of great importance in astrophysics for deriving information about the physical characteristics of hot optically thin plasma sources from their EUV and X-ray spectra. We describe ...
In this article, we develop a general method to obtain local limit theorems from distributional limit theorems. Our results use probabilistic arguments and yield explicit bounds on the quality of app...
We analyze the mean cost of the partial match queries in random two-dimensional quadtrees. The method is based on fragmentation theory. The convergence is guaranteed by a coupling argument of Markov c...
The concept of Probable Maximum Precipitation (PMP) is based on the assumptions that (a) there exists an upper physical limit of the precipitation depth over a given area at a particular geographical ...
This paper presents a knowledge learning diagnostic approach implemented in an educational system. Probabilistic inference is used here to diagnose knowledge understanding level and to reason about pr...
We propose a probabilistic framework for pricing derivatives, which acknowledges that information and beliefs are subjective. Market prices can be translated into implied probabilities. In particular,...
We propose a probabilistic framework for pricing derivatives, which acknowledges that information and beliefs are subjective. Market prices can be translated into implied probabilities. In particular,...
The probabilistic approach that was recently introduced by Kijko and Graham (1998,1999) was applied for the estimation of seismic hazard for various sites in Greece in terms of peak ground acceleratio...

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