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Applying an interpretable machine learning framework to study mobility inequity in the recovery phase of COVID-19 pandemic

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2019Modeling of transport demand – analyzing, calculating, and forecasting transport demand

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56 cited

2021Spatial and social disparities in the decline of activities during the COVID-19 lockdown in Greater London50 cited

2021Social inequalities in mobility during and following the COVID-19 associated lockdown of the Madrid metropolitan area in Spain48 cited

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2024Analyzing Key Factors Influencing Human Mobility Before and During COVID ‐19 With Explainable Machine Learning4 cited
2025Analyzing travel behavior differences across population groups: An explainable machine learning approach with big mobility data4 cited