IEEE

Reconstruction of Time-Varying Graph Signals via Sobolev Smoothness

Abstract: Graph Signal Processing (GSP) is an emerging research field that extends the concepts of digital signal processing to graphs. GSP has numerous applications in different areas such as sensor ...
IEEE

Spatial–Temporal Tensor Graph Convolutional Network for Traffic Speed Prediction

Abstract: Accurate traffic speed prediction is crucial for the guidance and management of urban traffic, which at the same time requires a model with a satisfactory computational burden and memory ...
Green Bay Press-Gazette

Not a 'math person?' No worries; here's how Green Bay area schools are changing math class

Schools are starting to switch from learning math through memorization to learning it by problem-solving, focusing on understanding concepts. Ashwaubenon added class time to math and ELA in middle ...
GitHub

Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).

Foreseeing Congestion using LSTM on Urban Traffic Flow Clusters ICSAI 2019 Keras; dataset: CityPulse Using LSTM and GRU neural network methods for traffic flow prediction IEEE YAC 2016 Keras; dataset: ...