24 citations · 31 across the 7 of their papers we have counts for
4 papers · 1 filter
Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement
Maria Despoina Siampou, Shushman Choudhury, Shang-Ling Hsu +2
Recent progress in geospatial foundation models highlights the importance of learning general-purpose representations for real-world locations, particularly points-of-interest (POI…
WaveGNN: Integrating Graph Neural Networks and Transformers for Decay-Aware Classification of Irregular Clinical Time-Series
Arash Hajisafi, Maria Despoina Siampou, Bita Azarijoo +2
Clinical time series are often irregularly sampled, with varying sensor frequencies, missing observations, and misaligned timestamps. Prior approaches typically address these irreg…
Poly2Vec: Polymorphic Fourier-Based Encoding of Geospatial Objects for GeoAI Applications
Maria Despoina Siampou, Jialiang Li, John Krumm +2
Encoding geospatial objects is fundamental for geospatial artificial intelligence (GeoAI) applications, which leverage machine learning (ML) models to analyze spatial information.…
Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting
Arash Hajisafi, Haowen Lin, Sina Shaham +4
Forecasting the number of visits to Points-of-Interest (POI) in an urban area is critical for planning and decision-making for various application domains, from urban planning and…