GitHub / RiccardoSpolaor / Verbal-Explanations-of-Spatio-Temporal-Graph-Neural-Networks-for-Traffic-Forecasting
An eXplainable AI system to elucidate short-term speed forecasts in traffic networks obtained by Spatio-Temporal Graph Neural Networks.
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PURL: pkg:github/RiccardoSpolaor/Verbal-Explanations-of-Spatio-Temporal-Graph-Neural-Networks-for-Traffic-Forecasting
Stars: 18
Forks: 2
Open issues: 0
License: mit
Language: Jupyter Notebook
Size: 118 MB
Dependencies parsed at: Pending
Created at: over 2 years ago
Updated at: 4 months ago
Pushed at: over 1 year ago
Last synced at: 3 months ago
Topics: congestion-analysis, explainable-ai, feature-importance, graph-neural-networks, mcts-algorithm, metr-la, monte-carlo-tree-search, natural-language-generation, natural-language-processing, nlp, outcomes-analytics, pems-bay, post-hoc-explanation, spatio-temporal-graph, speed-prediction, stgnn, traffic-forecasting, transparency, trustworthy-ai, xai