Category: 7. Maths
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Multi-modal sensor fusion towards three-dimensional airborne sonar imaging in hydrodynamic conditions
Hydrodynamic conditions In hydrodynamic conditions, the air–water interface is non-planar as a result of the water’s surface waves; this is in contrast to hydrostatic conditions where the water volume is in a steady state and has a planar surface. An important note for imaging in hydrodynamic conditions is that we can invoke a quasi-static assumption:…
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An interpretable hybrid predictive model of COVID-19 cases using autoregressive model and LSTM
The results include four sections: Model evaluations, Prediction, Interpretability, and Comparative study on the WHO datasets. In Model evaluations, we introduce the metrics we use to evaluate the models and on which we compare the models’ performances. In section Prediction, we exhibit the visualizations of several interesting trials and compare the numerical predictions and evaluations…
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A multi-view contrastive learning for heterogeneous network embedding
Li, Z., Lu, C., Yi, Y. & Gong, J. A hierarchical framework for interactive behaviour prediction of heterogeneous traffic participants based on graph neural network. IEEE Trans. Intell. Transp. Syst. 6, 66 (2021). Google Scholar Yu, J. et al. Self-supervised multi-channel hypergraph convolutional network for social recommendation. In Proceedings of the Web Conference 2021 413–424…
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A novel medical image segmentation approach by using multi-branch segmentation network based on local and global information synchronous learning
Implementation and evaluation methods All experiments used the Pytorch framework and were implemented on the RTX 3060 GPU. The batch size was 4, and each image was resized to 320 \(\times\) 320 and normalized by mean and standard deviation. We used an Adam as the network optimizer and set the initial learning rate to 0.001.…
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Efficient low temperature Monte Carlo sampling using quantum annealing
Spin glass The key feature of the quantum annealer is that it finds preferentially configurations which are close to the global energy minimum of the phase space. As a first illustration how to determine the low temperature thermodynamics from these configurations, we use a spin glass37,38 with random couplings, which is given by the Hamiltonian…
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Forecasting COVID-19 spreading through an ensemble of classical and machine learning models: Spain’s case study
Results In this section, we focus on the results and analysis of the models trained on Spain as a whole. We, nevertheless, provide in the Supplementary Materials (Analysis by autonomous community) a similar analysis for the 17 Spanish autonomous communities. Tables 4 and 5 show the MAPE and RMSE performance for the test set. Columns encode inputs…
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The most at-risk regions in the world for high-impact heatwaves
Western North America heatwave, June 2021 In June 2021, western North America experienced a record-breaking heatwave. In Lytton, British Columbia, temperatures of 49.6 °C were observed on June 29th, breaking the previous record by almost 5 °C28. The heatwave was associated with an unusual circulation pattern, with a blocking anticyclone leading to a stagnant warm air mass29.…
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Using surface plasmons to create programmable neural networks
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This is a summary of: Gao, X. et al. Programmable surface plasmonic neural networks for microwave detection and processing. Nat. Electron. https://doi.org/10.1038/s41928-023-00951-x (2023). Continue Reading News Source: www.nature.com
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The role of the big geographic sort in online news circulation among U.S. Reddit users
Kümpel, A. S., Karnowski, V. & Keyling, T. News sharing in social media: A review of current research on news sharing users, content, and networks. Soc. Media Soc. 1, 2056305115610141 (2015). Google Scholar Forgas, J. P. & Baumeister, R. The Social Psychology of Gullibility: Conspiracy Theories, Fake News and Irrational Beliefs (Routledge, 2019). Book Google…
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Martin Wainwright named director of the Institute for Data, Systems, and Society | MIT News
Martin Wainwright, the Cecil H. Green Professor in MIT’s departments of Electrical Engineering and Computer Science (EECS) and Mathematics, has been named the new director of the Institute for Data, Systems, and Society (IDSS), effective July 1. “Martin is a widely recognized leader in statistics and machine learning — both in research and in education.…