Implementation of "Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel"
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Updated
Jun 19, 2024 - Jupyter Notebook
Implementation of "Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel"
Convergence-theoretic reformulation of the Hodge Conjecture for K3 surfaces, with flow-based projection methods, numerical experiments, and symbolic generalizations to abelian varieties and Calabi–Yau threefolds.
Describe your numerical experiments
A MATLAB toolkit of benchmark functions for numerical experiments of optimization.
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Configuration-driven numerical experiment runner for harmonic measure-related research
Numerical experiment analyzing simplex method iteration counts across 500 randomly generated linear programs.
Experimental notes and Python implementations of Zeckendorf arithmetic, with empirical observations on simple physics test problems. Honest experimental research, not a finished paper.
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