Abstract: Graph pooling is crucial for enlarging the receptive field and reducing computational costs in deep graph representation learning. In this work, we propose a simple but effective graph ...
A comprehensive machine learning project that predicts UFC fight outcomes (KO/TKO vs Non-KO) based on round-by-round fighter statistics. This project analyzes Lightweight division fights using Random ...
Abstract: We investigated the possibilities of enhancement of the random-walk drift-diffusion (RWDD) simulations of charge transport in single-events phenomena by modeling electrostatic effects. We ...
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