A thermodynamic extension of information geometric regularization for compressible flows introduces an anisotropic stress tensor and an elliptic equation that mitigates cusp singularities in simulations while preserving inviscid benefits.
Nature525(7567), 47–55 (2015)
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Probabilistic bias correction doubles AI subseasonal forecast skill and wins a 2025 international competition by correcting biases in ECMWF models for pressure, temperature, and precipitation.
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Thermodynamically Constrained Information Geometric Regularization for Compressible Flows
A thermodynamic extension of information geometric regularization for compressible flows introduces an anisotropic stress tensor and an elliptic equation that mitigates cusp singularities in simulations while preserving inviscid benefits.
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Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction
Probabilistic bias correction doubles AI subseasonal forecast skill and wins a 2025 international competition by correcting biases in ECMWF models for pressure, temperature, and precipitation.