Abstract: The spatiotemporal dynamics of traffic forecasting make it a challenging task. In recent years, by adapting to the topology of traffic networks where road segments serve as nodes, graph ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

According to mathematical legend, Peter Sarnak and Noga Alon made a bet about optimal graphs in the late 1980s. They’ve now both been proved wrong. It started with a bet. In the late 1980s, at a ...

Abstract: Graph Convolutional Networks (GCNs) have emerged as a leading approach for semi-supervised node classification. However, due to the uneven distribution of labeled nodes in graphs, only a ...