Machine learning cloud microphysics parameterization achieves stable decade-long online coupling in ICON with performance comparable to the classical graupel scheme while eliminating two tuning parameters.
Opening strategies in the game of go from feudalism to superhuman AI
4 Pith papers cite this work. Polarity classification is still indexing.
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Machine learning models recover most warm-rain and ice microphysical process rates from standard ICON model outputs for accumulation intervals of 10 minutes or less using a two-step classification-regression approach with calibrated uncertainty.
A novel agent-based model integrating optimal distinctiveness and cognitive compression via entropy generates emergent heterogeneous opinion clusters that continue to evolve dynamically.
The historical sequence of papal names is consistent with a random-copying process with innovation, as predicted by Ewens sampling theory and the Chinese restaurant process.
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Quo nomine vis vocari? A random-copying model explains the temporal sequence of papal names
The historical sequence of papal names is consistent with a random-copying process with innovation, as predicted by Ewens sampling theory and the Chinese restaurant process.