Context-Aware Learning for Generative Models

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Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

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This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

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The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

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Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although rec ...

Context-Aware Learning for Generative Models

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Recovering Static and Time-Varying Communities Using Persistent Edges

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Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Text-to-Microstructure Generation Using Generative Deep Learning