Empirical analysis of the Laplace and neural tangent kernel reproducing kernel Hilbert space (RKHS)
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Aug 18, 2022 - Jupyter Notebook
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reproducing-kernel-hilbert-space
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This is the recent work of my on the importance and application of mathematical function around its Hilbert function theory on artificial intelligence algorithms. The main motivation was the desire of improving the convergence rate and learning rate of various learning algorithms via Generalized Gaussian Radial Basis Function.
deep-neural-networks deep-learning neural-network machine-learning-algorithms artificial-intelligence image-recognition support-vector-machine kernel-regression gaussian-process-regression activation-functions reproducing-kernel-hilbert-space
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Mar 13, 2024 - MATLAB
This research work is about Limited Data Acquisition for the real life physical experiment of fluid flow across cylinder based on Kernelized Extended Dynamic Mode Decomposition by incorporating Gaussian Random Matrix Theory and Laplacian Kernel Function Hilbert space.
julia-language random-matrix-theory dynamic-mode-decomposition reproducing-kernel-hilbert-space laplacian-kernel koopman-operator-theory gaussian-random-vector
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Mar 13, 2024 - Python
Discretized Wasserstein Particle Flows of a MMD-regularized f-divergence functional.
mmd regularization sampling rkhs gradient-flow sampling-methods f-divergence wasserstein-gradient-flows particle-flow reproducing-kernel-hilbert-space
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Dec 20, 2024 - Python
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