1,721,052 research outputs found
Learning Fractional White Noises in Neural Stochastic Differential Equations
No full textDifferential equations play important roles in modeling complex physical systems. Recent advances present interesting research directions by combining differential equations with neural networks. By including noise, stochastic differential equations (SDEs) allows us to model data with uncertainty and measure imprecision. There are many variants of noises known to exist in many real-world data. For
example, previously white noises are idealized and induced by Brownian motions. Nevertheless, there is a lack of machine learning models that can handle such noises. In this paper, we introduce a generalized fractional white noise to existing models and propose an efficient approximation of noise sample paths based on classical integration methods and sparse Gaussian processes. Our experimental results demonstrate that the proposed model can capture noise characteristics such as continuity from various time series data, therefore improving model fittings over existing models.
We examine how we can apply our approach to score-based generative models, showing that there exists a case of our generalized noise resulting in a better image generation measure
Automatic detection of weeds: synergy between EfficientNet and transfer learning to enhance the prediction accuracy
Get PDFThe application of digital technologies to facilitate farming activities has been on the rise in recent years. Among different tasks, the classification of weeds is a prerequisite for smart farming, and various techniques have been proposed to automatically detect weeds from images. However, many studies deal with weed images collected in the laboratory settings, and this might not be applicable to real-world scenarios. In this sense, there is still the need for robust classification systems that can be deployed in the field. In this work, we propose a practical solution to recognition of weeds exploiting two versions of EfficientNet as the recommendation engine. More importantly, to make the learning more effective, we also utilize different transfer learning strategies. The final aim is to build an expert system capable of accurately detecting weeds from lively captured images. We evaluate the approach's performance using DeepWeeds, a real-world dataset with 17,509 images. The experimental results show that the application of EfficientNet and transfer learning on the considered dataset substantially improves the overall prediction accuracy in various settings. Through the evaluation, we also demonstrate that the conceived tool outperforms various state-of-the-art baselines. We expect that the proposed framework can be installed in robots to work on rice fields in Vietnam, allowing farmers to find and eliminate weeds in an automatic manner
SigFormer: Signature Transformers for Deep Hedging
No full textDeep hedging is a promising direction in quantitative finance, incorporating models and techniques from deep learning research. While giving excellent hedging strategies, models inherently requires careful treatment in designing architectures for neural networks. To mitigate such difficulties, we introduce SigFormer, a novel deep learning model that combines the power of path signatures and transformers to handle sequential data, particularly in cases with irregularities. Path signatures effectively capture complex data patterns, while transformers provide superior sequential attention. Our proposed model is empirically compared to existing methods on synthetic data, showcasing faster learning and enhanced robustness, especially in the presence of irregular underlying price data. Additionally, we validate our model performance through a real-world backtest on hedging the S&P 500 index, demonstrating positive outcomes
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
INTERNATIONALIZATION AND MACROECONOMIC MANAGEMENT IN VIETNAM: SOME LESSONS FROM SWEDISH EXPERIENCES
Get PDFThe main macroeconomic challenges at the early stages of Vietnam¡¯s economic reforms were related to stability and growth. The main achievements of Doi Moi are also related to the success in meeting these two challenges: Vietnam has managed to combine high growth with reasonable price stability since the early 1990s. However, meeting these challenges has become more difficult over time as new challenges have emerged. In the mid-1990s, economic structure and external balance entered the policy debate. In the late 1990s, the Asian crisis created further problems. In recent years, issues related to social and regional development gaps and investment quality have become important policy objectives. At the same time, it is clear that the instruments for economic policy making have changed. While the challenges of the early 1990s could be handled with various direct interventions like credit ceilings and quantitative trade restrictions, indirect instruments for macroeconomic management are gradually becoming more important. For instance, the choice of exchange rate regime is becoming much more important than in the past. This paper summarizes Vietnam¡¯s macroeconomic development, and illustrates some of the alternative approaches to macroeconomic management in an increasingly internationalized and deregulated environment by recounting some experiences from Swedish macroeconomic management during the past three decades.Vietnam; internationalization; macroeconomic management; growth; stability
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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