11 citations · 11 across the 18 of their papers we have counts for
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CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data
Francis Ndikum Nji, Vandana Janeja, Jianwu Wang
Deep subspace clustering plays a critical role in applications involving multivariate spatiotemporal data, such as sea ice monitoring, disease spread analysis, and tracking neuro-d…
Knowledge-Guided Time-Varying Causal Inference for Arctic Sea Ice Dynamics
Akila Sampath, Vandana Janeja, Jianwu Wang
Quantifying the causal relationship between sea ice thickness and sea surface height (SSH) is essential for understanding the mechanisms driving polar climate dynamics. Conventiona…
Physics-Encoded Inverse Modeling for Arctic Snow Depth Estimation
Akila Sampath, Vandana P. Janeja, Jianwu Wang
Accurate estimation of unobserved quantities in time-varying inverse problems remains challenging when observations are sparse and only indirectly related to the target variable. I…
Attention-Guided Deep Adversarial Temporal Subspace Clustering (A-DATSC) Model for multivariate spatiotemporal data
Francis Ndikum Nji, Vandana Janeja, Jianwu Wang
Deep subspace clustering models are vital for applications such as snowmelt detection, sea ice tracking, crop health monitoring, infectious disease modeling, network load predictio…
B-TGAT: A Bi-directional Temporal Graph Attention Transformer for Clustering Multivariate Spatiotemporal Data
Francis Ndikum Nji, Vandana Janaja, Jianwu Wang
Clustering high-dimensional multivariate spatiotemporal climate data is challenging due to complex temporal dependencies, evolving spatial interactions, and non-stationary dynamics…
IDRIFTNET: Physics-Driven Spatiotemporal Deep Learning for Iceberg Drift Forecasting
Rohan Putatunda, Sanjay Purushotham, Ratnaksha Lele +1
Drifting icebergs in the polar oceans play a key role in the Earth's climate system, impacting freshwater fluxes into the ocean and regional ecosystems while also posing a challeng…