1 citations · 2 across the 4 of their papers we have counts for
4 papers
Explaining latent representations of generative models with large multimodal models
Mengdan Zhu, Zhenke Liu, Bo Pan +2
Learning interpretable representations of data generative latent factors is an important topic for the development of artificial intelligence. With the rise of the large multimodal…
SurroCBM: Concept Bottleneck Surrogate Models for Generative Post-hoc Explanation
Bo Pan, Zhenke Liu, Yifei Zhang +1
Explainable AI seeks to bring light to the decision-making processes of black-box models. Traditional saliency-based methods, while highlighting influential data segments, often la…
Large Language Models for Spatial Trajectory Patterns Mining
Zheng Zhang, Hossein Amiri, Zhenke Liu +2
Identifying anomalous human spatial trajectory patterns can indicate dynamic changes in mobility behavior with applications in domains like infectious disease monitoring and elderl…
Graph Neural Network for spatiotemporal data: methods and applications
Yun Li, Dazhou Yu, Zhenke Liu +3
In the era of big data, there has been a surge in the availability of data containing rich spatial and temporal information, offering valuable insights into dynamic systems and pro…