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Author

Runlong Yu

4 papers indexed here

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#machine learning Preprint Sep 2026

Staying on the Attractor: Supervising Neural Surrogates of 3D Turbulence Where They Leave It

This work proposes off-attractor supervision (OAS) to supervise neural surrogates where they leave the attractor and integrates physical models into neural simulation by extending supervision from fixed reference trajectories to states where the surrogate is likely to fail.

Yi-Long Dai, Shaswata Mitra, Raj Patel et al. · 0 citations
#machine learning Preprint Aug 2026

SolarFlowRefiner: Refinement-Aware Flow Matching for Surface Solar Radiation Downscaling

High-resolution surface solar radiation (SSR) is important for solar forecasting and grid operation. However, physically consistent reanalysis products are too coarse to resolve localized cloud-driven variability. In this paper, we study a multisource downscaling task that reconstructs high-resolution SolarCube SSR fie...

U. Srivastava, Antonita Racheal, Yi-Heng Chen et al. · 0 citations
Book Open access May 2025

LLM-based Evaluation Policy Extraction for Ecological Modeling

Evaluating ecological time series is critical for benchmarking model performance in many important applications, including predicting greenhouse gas fluxes, tracking soil moisture and soil–atmosphere interactions, and monitoring hydrological cycles. Traditional numerical metrics (e.g., R-squared, root mean square error...

Qi Cheng, Licheng Liu, Yi-Xuan Chen et al. · 3 citations
Book Open access Aug 2026

LLM-based Evaluation Policy Extraction for Ecological Modeling

Evaluating ecological time series is critical for benchmarking model performance in many important applications, including predicting greenhouse gas fluxes, tracking soil moisture and soil–atmosphere interactions, and monitoring hydrological cycles. Traditional numerical metrics (e.g., R-squared, root mean square error...

Qi Cheng, Licheng Liu, Yixuan Chen et al. · 0 citations

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