aprbw

traffic_prediction

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

G-SWaN

G-SWaN: G-SWaN: Graph Self-attention WaveNet for Traffic Forecasting. This is the official repo for the following paper: Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting (IoTDI '23)

flight_delay_01

Predicting Flight Delay With Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map

OoD_Electricity_Forecasting_during_COVID-19

aprbw.github.io

EpochAndBatches

Simple deep learning experiment tracker.

forecasting-on-new-roads

git_training_01

graph_partition_based_DCRNN

pygcn

Graph Convolutional Networks in PyTorch

pytorch-GAT

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!