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.
Morphological Change
6 Pith papers cite this work. Polarity classification is still indexing.
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Syntactic belief update via generalized Rényi divergence on syntactic trees predicts garden path reading times better than lexical surprisal.
Multi-agent simulations with naturalistic lexicons and phonological rules show scale-free networks and Bernoulli adoption produce more plausible morphologies, evaluated by an LLM historical linguist debate system and tested via historical case studies.
An integrated multi-hazard risk framework applied to the US high-voltage grid finds tropical cyclone wind causes the highest expected daily damage ($137M) while tornadoes drive the largest downstream economic losses ($4.93B/day), with a compound freezing rain/wind scenario producing the most severe
A tool combining full hydrodynamic modeling with a bespoke evolutionary algorithm to optimize blue-green infrastructure for reducing urban flood vulnerability at property scale.
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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Syntactic Belief Update as the Driver of Garden Path Processing Difficulty
Syntactic belief update via generalized Rényi divergence on syntactic trees predicts garden path reading times better than lexical surprisal.
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Agent-based models for the evolution of morphological alternation patterns
Multi-agent simulations with naturalistic lexicons and phonological rules show scale-free networks and Bernoulli adoption produce more plausible morphologies, evaluated by an LLM historical linguist debate system and tested via historical case studies.
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A Comparative Multi-Hazard Risk Assessment of the US High-Voltage Transmission Network
An integrated multi-hazard risk framework applied to the US high-voltage grid finds tropical cyclone wind causes the highest expected daily damage ($137M) while tornadoes drive the largest downstream economic losses ($4.93B/day), with a compound freezing rain/wind scenario producing the most severe
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Optimising Urban Flood Resilience
A tool combining full hydrodynamic modeling with a bespoke evolutionary algorithm to optimize blue-green infrastructure for reducing urban flood vulnerability at property scale.
- Evaluating the Evaluator: Problems with SemEval-2020 Task 1 for Lexical Semantic Change Detection