We use physics-guided semi-supervised learning to align human-labeled wildfire smoke annotations with GOES satellite imagery, creating SmokeViz, a large-scale dataset for smoke plume segmentation.

We propose a new prediction market framework with close ties to general steepest descent.

We present a practical characterization of statistical consistency for differentiable surrogate losses