DustNET is proposed as a shared dataset to train machine learning models that complement traditional physics equations for predictive modeling of dusty plasmas across laboratory and natural scales.
Physics-informed meta-instrument for exper- iments (pimix) with applications to fusion energy
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PiMiX 2.0 extends prior PiMiX work into an AI-enhanced framework for multimodal RadIT data ingestion, 3D/4D reconstruction, and physics-aware interpretation.
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DustNET: enabling machine learning and AI models of dusty plasmas
DustNET is proposed as a shared dataset to train machine learning models that complement traditional physics equations for predictive modeling of dusty plasmas across laboratory and natural scales.
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PiMiX 2.0: AI-enhanced Data Fusion for Radiographic Imaging and Tomography
PiMiX 2.0 extends prior PiMiX work into an AI-enhanced framework for multimodal RadIT data ingestion, 3D/4D reconstruction, and physics-aware interpretation.