1,720,965 research outputs found
Generative Models as Out-of-equilibrium particle systems: the case of Energy-Based Models
Get PDFL'abstract è presente nell'allegato / the abstract is in the attachmen
WhaleNet: A Novel Deep Learning Architecture for Marine Mammals Vocalizations on Watkins Marine Mammal Sound Database
Get PDFMarine mammal communication is a complex field, hindered by the diversity of vocalizations and environmental factors. Accurate classification of these vocalizations is critical for understanding species behavior, monitoring population trends, and assessing the impact of human activities on marine life. However, current classification approaches face significant challenges due to the wide range of vocalization types and environmental noise. The Watkins Marine Mammal Sound Database (WMMD) constitutes a comprehensive labeled dataset employed in machine learning applications. Nevertheless, the methodologies for data preparation, preprocessing, and classification documented in the literature exhibit considerable variability and are typically not applied to the dataset in its entirety. This study initially undertakes a concise review of the state-of-the-art benchmarks pertaining to the dataset, with a particular focus on clarifying data preparation and preprocessing techniques. Subsequently, we explore the utilization of the Wavelet Scattering Transform (WST) and Mel spectrogram as preprocessing mechanisms for feature extraction. In this paper, we introduce WhaleNet (Wavelet Highly Adaptive Learning Ensemble Network), a sophisticated deep ensemble architecture for the classification of marine mammal vocalizations, leveraging both WST and Mel spectrogram for enhanced feature discrimination. By addressing the inconsistencies in data preparation and by utilizing advanced preprocessing techniques, our approach provides a more robust framework for classifying marine mammal vocalizations, which is essential for conservation efforts and behavioral research. By integrating the insights derived from WST and Mel representations, we achieved an improvement in classification accuracy by 8-10% over existing architectures, corresponding to a classification accuracy of 97.61%
Efficient Training of Energy-Based Models Using Jarzynski Equality
Get PDFEnergy-based models (EBMs) are generative models inspired by statistical physics
with a wide range of applications in unsupervised learning. Their performance
is well measured by the cross-entropy (CE) of the model distribution relative
to the data distribution. Using the CE as the objective for training is however
challenging because the computation of its gradient with respect to the model
parameters requires sampling the model distribution. Here we show how results for
nonequilibrium thermodynamics based on Jarzynski equality together with tools
from sequential Monte-Carlo sampling can be used to perform this computation
efficiently and avoid the uncontrolled approximations made using the standard
contrastive divergence algorithm. Specifically, we introduce a modification of the
unadjusted Langevin algorithm (ULA) in which each walker acquires a weight that
enables the estimation of the gradient of the cross-entropy at any step during GD,
thereby bypassing sampling biases induced by slow mixing of ULA. We illustrate
these results with numerical experiments on Gaussian mixture distributions as
well as the MNIST and CIFAR-10 datasets. We show that the proposed approach
outperforms methods based on the contrastive divergence algorithm in all the
considered situations
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
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
Time Reversal Symmetry for Classical, Nonrelativistic Quantum and Spin Systems in Presence of Magnetic Fields
Get PDFWe extend to quantum mechanical systems results previously obtained for
classical mechanical systems, concerning time reversibility in presence of a
magnetic field. As in the classical case, results like the Onsager reciprocal
relations are consequently obtained, without recourse to the Casimir
modification. The quantum systems treated here are nonrelativistic, and are
described by the Schr{\"o}dinger equation or the Pauli equation. In particular,
we prove that the spin-field interaction does not break the time reversal
invariance (TRI) of the dynamics, and that it does not require additional
conditions for such a symmetry to hold, compared to the spinless cases
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