Optimizing training data via a differentiable SCM yields climate emulators that outperform those trained on six standard ScenarioMIP pathways while using less data and isolating distinct forcing responses.
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3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
A new optimization algorithm with double machine learning for wildfire spread estimation enables better crew assignments that reduce total area burned.
A decentralized optimization-based controller for multi-UAV wildfire suppression ensures safety and energy sufficiency using control Lyapunov and barrier functions under uncertainties.
citing papers explorer
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Optimal scenario design for climate emulation
Optimizing training data via a differentiable SCM yields climate emulators that outperform those trained on six standard ScenarioMIP pathways while using less data and isolating distinct forcing responses.
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Predictive and Prescriptive AI toward Optimizing Wildfire Suppression
A new optimization algorithm with double machine learning for wildfire spread estimation enables better crew assignments that reduce total area burned.
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Safe and Energy-Aware Decentralized PDE-Constrained Optimization-Based Control of Multi-UAVs for Persistent Wildfire Suppression
A decentralized optimization-based controller for multi-UAV wildfire suppression ensures safety and energy sufficiency using control Lyapunov and barrier functions under uncertainties.