3 citations · 3 across the 4 of their papers we have counts for
5 papers
Planetary Geospatial Foundation Models: A New Paradigm for Global Public Health
Arbaaz Muslim, Aviv Slobodkin, Katherine Wheeler-Martin +35
The efficacy of traditional disease prediction is limited by spatial gaps and temporal lags, which impact the timing and targets of resource deployments. Outbreaks escalate undetec…
Hierarchical Clustering With Confidence
Di Wu, Jacob Bien, Snigdha Panigrahi
Agglomerative hierarchical clustering is one of the most widely used approaches for exploring how observations in a dataset relate to each other. However, its greedy nature makes i…
Earth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning
Aaron Bell, Amit Aides, Amr Helmy +57
Geospatial data offers immense potential for understanding our planet. However, the sheer volume and diversity of this data along with its varied resolutions, timescales, and spars…
Reluctant Interaction Inference after Additive Modeling
Yiling Huang, Snigdha Panigrahi, Guo Yu +1
Additive models enjoy the flexibility of nonlinear models while still being readily understandable to humans. By contrast, other nonlinear models, which involve interactions betwee…
Quantifying uncertainty and stability among highly correlated predictors: a subspace perspective
Xiaozhu Zhang, Jacob Bien, Armeen Taeb
We study the problem of linear feature selection when features are highly correlated. Such settings pose two fundamental challenges. First, how should model similarity be defined?…