New study published in Transportation Research Interdisciplinary Perspectives

Our paper on “A causal intervention framework for synthesizing mobility data and evaluating predictive neural networks” has been published open-source in Transportation Research Interdisciplinary Perspectives!

We introduced a Causal Intervention Framework that enables controlled manipulation of mobility-related behavior in synthetic location sequences. This enables us to evaluate how specific behaviors influence the performance of next-location prediction models.

We hope this offers a foundation for future research at the intersection of mobility modeling, interpretation, and explainable AI.

Check out the paper online and the corresponding code on Github!