Revision is a crucial step in scientific writing, where authors refine their work to improve clarity, structure, and academic quality. Existing approaches automated writing assistance often focus on sentence-level revisions, which fail capture the broader context needed for effective modification. In this paper, we explore impact of shifting from paragraph-level scope task text revision. The paragraph level definition allows more meaningful changes, guided by detailed revision instructions...

Abstract Joint fine-mapping that leverages information between quantitative traits could improve accuracy and resolution over single-trait fine-mapping. Using summary statistics, flashfm (flexible shared fine-mapping) fine-maps signals for multiple traits, allowing missing trait measurements use of related individuals. In a Bayesian framework, prior model probabilities are formulated to favour combinations share causal variants capitalise on traits. Simulation studies demonstrate both...

We propose a definition of entropy for stochastic processes. provide reproducing kernel Hilbert space model to estimate from random sample realizations process, namely functional data, and introduce two approaches minimum sets. These sets are relevant detect anomalous or outlier data. A numerical experiment illustrates the performance proposed method; in addition, we conduct an analysis mortality rate curves as interesting application real-data context explore anomaly detection.

Abstract In this paper, we propose a novel approach to address the problem of functional outlier detection. Our method leverages low-dimensional and stable representation functions using Reproducing Kernel Hilbert Spaces (RKHS). We define depth measure based on density kernels that satisfy desirable properties. also challenges associated with estimating kernel depth. Throughout Monte Carlo simulation assess performance our in detection task under different scenarios. To illustrate...

Since the advent of word embedding methods, representation longer pieces texts such as sentences and paragraphs is gaining more interest, especially for textual similarity tasks.Mikolov et al. (2013a) have demonstrated that words phrases exhibit linear structures allow to meaningfully combine by an element-wise addition their vector representations.Recently, Arora ( 2017) shown removing projections weighted average sum vectors on first principal components, outperforms sophisticated...

Les systèmes de recherche d'information renvoient généralement une liste ordonnée documents, où seuls le titre et parfois un extrait comportant les mots la requête permettent d'en évaluer pertinence pour son besoin initial. Ces types résultat conduisent toujours à devoir consulter nombreux documents réellement trouver des réponses pertinentes. Afin d'éviter cet écueil nous sommes intéressés visualisation d'un texte : que doit-on montrer comment ? Dans notre système, RÉGAL (RÉsumé Guidé par...

Most work in text retrieval aims at presenting the information held by several texts order to give entry clues towards these and allow a navigation between them. Besides, lesser interest is dedicated definition of principles for accessing content single documents. As most systems return documents from an initial request made words, usual solution consists document titles highlighting words inside passage or whole document. Such presentation does not rapid reading cannot satisfy themselves...

Functional Time Series (FTS) are sequences of dependent random elements taking values on some functional space. Most the research this domain focuses producing a predictor able to forecast next function, having observed part sequence. For this, Autoregressive Hilbertian process is suitable framework. Here, we address problem constructing simultaneous predictive confidence bands for stationary FTS. The method based an entropy measure stochastic processes. To construct bands, use Reproducing...

ABSTRACT Gaussian processes and the Kullback–Leibler divergence have been deeply studied in statistics machine learning. This paper marries these two concepts introduce local to learn about intervals where differ most. We address subtleties entailed estimation of divergences corresponding interval maximum as well. The performance numerical efficiency proposed method are showcased via a Monte Carlo simulation study. In medical research context, we assess potential devised tools analysis...

This paper explores the detection of derivation links between texts (otherwise called plagiarism, near-duplication, revision, etc.) at document level. We evaluate use textual elements implementing ideas specificity and invariance as well as their combination to characterize derivatives. built a French press corpus based on Wikinews revisions run this evaluation. obtain performances similar state the art method (n-grams overlap) while reducing signature size and so, processing costs....