most citedSpatially Regularized Graph Attention Autoencoder Framework for Detecting Rainfall Extremes

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Physiologically Active Vegetation Reverses Its Cooling Effect in Humid Urban Climates

Angana Borah, Adrija Datta, Ashish S. Kumar +2

Efforts to green cities for cooling are succeeding unevenly because the same vegetation that cools surfaces can also intensify how hot the air feels. Previous studies have identifi…

cs.AI2025

Physics-guided Emulators Reveal Resilience and Fragility under Operational Latencies and Outages

Sarth Dubey, Subimal Ghosh, Udit Bhatia

Reliable hydrologic and flood forecasting requires models that remain stable when input data are delayed, missing, or inconsistent. However, most advances in rainfall-runoff predic…

q-bio.PE2025

Temporally staggered cropping co-benefits beneficial insects and pest control globally

Adrija Datta, Subramanian Sankaranarayanan, Udit Bhatia

Reconciling increasing food production with biodiversity conservation is critical yet challenging, particularly given global declines in beneficial insects driven by monoculture in…

q-bio.PE2025

Warming demands extensive tropical but minimal temperate management in plant-pollinator networks

Adrija Datta, Sarth Dubey, Tarik C. Gouhier +2

Anthropogenic warming impacts ecological communities and disturbs species interactions, particularly in temperature sensitive plant pollinator networks. While previous assessments…

cs.LG20241 cited

Spatially Regularized Graph Attention Autoencoder Framework for Detecting Rainfall Extremes

Mihir Agarwal, Progyan Das, Udit Bhatia

We introduce a novel Graph Attention Autoencoder (GAE) with spatial regularization to address the challenge of scalable anomaly detection in spatiotemporal rainfall data across Ind…