Gaussian process regression enables implicit multi-camera calibration by learning 2D-to-3D mappings with built-in uncertainty and active learning for efficient data use.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
A new tail dependence measure for linear processes with regularly varying distributions is introduced, incorporating persistence effects and validated via simulations and cryptocurrency data analysis.
A cascade pipeline on 400 AIE tiles evaluates gg→ttg leading-order matrix elements at 1 million per second with parts-per-million accuracy to MadGraph, delivering 34× CPU speedup and 7.7× better energy efficiency at 54.8 W.
citing papers explorer
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Implicit Multi-Camera System Calibration Using Gaussian Processes
Gaussian process regression enables implicit multi-camera calibration by learning 2D-to-3D mappings with built-in uncertainty and active learning for efficient data use.
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Measuring Tail Dependence in Linear Processes: Theory and Empirics
A new tail dependence measure for linear processes with regularly varying distributions is introduced, incorporating persistence effects and validated via simulations and cryptocurrency data analysis.
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Cascade Pipeline for Leading-Order Matrix Element Evaluation on AMD Versal AI Engine Arrays
A cascade pipeline on 400 AIE tiles evaluates gg→ttg leading-order matrix elements at 1 million per second with parts-per-million accuracy to MadGraph, delivering 34× CPU speedup and 7.7× better energy efficiency at 54.8 W.