High-dimensional learning of narrow neural networks

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Reduced basis methods for time-dependent problems

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Numerical simulation of parametrized differential equations is of crucial importance in the study of real-world phenomena in applied science and engineering. Computational methods for real-time and many-query simulation of such problems often require prohi ...

CAMBRIDGE UNIV PRESS2022

Latent Space Slicing for Enhanced Entropy Modeling in Learning-Based Point Cloud Geometry Compression

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The growing adoption of point clouds as an imaging modality has stimulated the search for efficient solutions for compression. Learning-based algorithms have been reporting increasingly better performance and are drawing the attention from the research com ...

IEEE2022

A machine learning-driven two-phase metaheuristic for autonomous ridesharing operations

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This paper contributes to the intersection of operations research and machine learning in the context of autonomous ridesharing. In this work, autonomous ridesharing operations are reproduced through an event-based simulation approach and are modeled as a ...

PERGAMON-ELSEVIER SCIENCE LTD2022