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Author

Arin Gopakumar

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#machine learning Preprint Aug 2026

WildfireSpreadBench: The Metric Decides the Model in Wildfire Spread Prediction

Machine learning is being increasingly used to predict where active wildfires will burn the following day, helping inform evacuation boundaries and containment lines. Most models are evaluated using Average Precision (AP), which summarizes performance across all decision thresholds, although acting on a forecast requir...

Arin Gopakumar, Marco Pannozzo · 0 citations
#machine learning Preprint Aug 2026

HOPPER: Learnable Hop Extraction for Linearized Graph Sequence Models

HOPPER is introduced, an end-to-end learnable extension of LGSM that learns how hop sequences should be extracted before processing by a modern state-space model, and demonstrates that learnable sequence extraction is a flexible and effective framework for long-range graph representation learning across synthetic, phys...

Isuru Herath, Arin Gopakumar, Sharan Sahu · 0 citations

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