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Functional Analysis

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Functional Analysis

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Research Frontiers in Reproducing Kernel Hilbert Spaces

Analysis of RKHS theory with applications to machine learning, approximation theory, and integral operators.

Kernel Operators in Non-Euclidean Metric Spaces
Reproducing Kernels and Quantum Information Geometry
Sparse Representation Learning via Kernel Approximation
Adaptive Kernel Hilbert Spaces for Inverse Problems
Kernelized Neural Operators for PDE Discovery
Signature Kernels and Infinite-Dimensional Path Analysis
Optimal Transport Metrics in RKHS Framework
Spectral Properties of Non-Stationary Reproducing Kernels
Kernel Methods for Functional Data in Manifolds
Graph Kernels and Topological Feature Extraction

All Functional Analysis PhD categories