1,720,957 research outputs found
Cavity-Based Approaches to Stochastic Dynamics on Sparse Graphs: From Ecological Systems to Epidemiological Inference
Get PDFL'abstract è presente nell'allegato / the abstract is in the attachmen
Small-coupling dynamic cavity: A Bayesian mean-field framework for epidemic inference
Get PDFA novel generalized mean-field approximation, called the small-coupling dynamic cavity (SCDC) method, for epidemic inference and risk assessment is presented. The method is developed within a fully Bayesian framework and accounts for noncausal effects generated by the presence of observations. It is based on a graphical model representation of the epidemic stochastic process and utilizes dynamic cavity equations to derive a set of self-consistent equations for probability marginals defined on the edges of the contact graph. By performing a small-coupling expansion, a pair of time-dependent cavity messages is obtained, which capture the probability of individual infection and the conditioning power of observations. In its efficient formulation, the computational cost per iteration of the SCDC algorithm is linear in the duration of the epidemic dynamics. While the method is derived for the susceptible-infected (SI) model, it is straightforwardly applicable to many other Markovian epidemic processes, including recurrent ones. This linear complexity is particularly advantageous for recurrent epidemic processes, where inference methods are typically exponentially complex in the duration of the epidemic dynamics. The method exhibits high accuracy in assessing individual risk, as demonstrated by tests on the SI model applied to various classes of synthetic contact networks, where it performs on par with belief propagation techniques and generally exceeds the performance of individual-based mean-field methods. Additionally, the method was applied to recurrent epidemic models, where it showed interesting performance even for relatively large values of the infection probability, highlighting its versatility and effectiveness in challenging scenarios. Although convergence issues may arise due to long-range correlations in contact graphs, the estimated marginal probabilities remain sufficiently accurate for reliable risk estimation. Future work includes extending the method to non-Markovian recurrent epidemic models and investigating the role of second-order terms in the small-coupling expansion of the observation-reweighted dynamic cavity equations
Gaussian approximation of dynamic cavity equations for linearly-coupled stochastic dynamics
Get PDFStochastic dynamics on sparse graphs and disordered systems often lead to complex behaviors characterized by heterogeneity in time and spatial scales, slow relaxation, localization, and aging phenomena. The mathematical tools and approximation techniques required to analyze these complex systems are still under development, posing significant technical challenges and resulting in a reliance on numerical simulations. We introduce a novel computational framework for investigating the dynamics of sparse disordered systems with continuous degrees of freedom. Starting with a graphical model representation of the dynamic partition function for a system of linearly-coupled stochastic differential equations, we use dynamic cavity equations on locally tree-like factor graphs to approximate the stochastic measure. Here, cavity marginals are identified with local functionals of single-site trajectories. Our primary approximation involves a second-order truncation of a small-coupling expansion, leading to a Gaussian form for the cavity marginals. For linear dynamics with additive noise, this method yields a closed set of causal integro-differential equations for cavity versions of one-time and two-time averages. These equations provide an exact dynamical description within the local tree-like approximation, retrieving classical results for the spectral density of sparse random matrices. Global constraints, non-linear forces, and state-dependent noise terms can be addressed using a self-consistent perturbative closure technique. The resulting equations resemble those of dynamical mean-field theory in the mode-coupling approximation used for fully-connected models. However, due to their cavity formulation, the present method can also be applied to ensembles of sparse random graphs and employed as a message-passing algorithm on specific graph instances
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Gaussian approximation of dynamic cavity equations for linearly-coupled stochastic dynamics
Get PDFStochastic dynamics on sparse graphs and disordered systems often lead to
complex behaviors characterized by heterogeneity in time and spatial scales,
slow relaxation, localization, and aging phenomena. The mathematical tools and
approximation techniques required to analyze these complex systems are still
under development, posing significant technical challenges and resulting in a
reliance on numerical simulations. We introduce a novel computational framework
for investigating the dynamics of sparse disordered systems with continuous
degrees of freedom. Starting with a graphical model representation of the
dynamic partition function for a system of linearly-coupled stochastic
differential equations, we use dynamic cavity equations on locally tree-like
factor graphs to approximate the stochastic measure. Here, cavity marginals are
identified with local functionals of single-site trajectories. Our primary
approximation involves a second-order truncation of a small-coupling expansion,
leading to a Gaussian form for the cavity marginals. For linear dynamics with
additive noise, this method yields a closed set of causal integro-differential
equations for cavity versions of one-time and two-time averages. These
equations provide an exact dynamical description within the local tree-like
approximation, retrieving classical results for the spectral density of sparse
random matrices. Global constraints, non-linear forces, and state-dependent
noise terms can be addressed using a self-consistent perturbative closure
technique. The resulting equations resemble those of dynamical mean-field
theory in the mode-coupling approximation used for fully-connected models.
However, due to their cavity formulation, the present method can also be
applied to ensembles of sparse random graphs and employed as a message-passing
algorithm on specific graph instances.Comment: 44 pages, 5 figures (including supplemental material
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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