An Introduction to the Theory of Reproducing Kernel Hilbert Spaces

By Vern I. Paulsen, M. Raghupathi. 2016

689 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/440218056738e05b5ab43679f932a9f33fccee87

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Feliks Nuske
2. Sebastian Peitz

In Control and Systems Engineering

1. Manuel Schaller
2. Feliks Nuske
3. Sebastian Peitz

In Statistical and Nonlinear Physics

1. Sebastian Peitz
2. Manuel Schaller
3. Karl Worthmann
4. Friedrich M. Philipp
5. Feliks Nuske
6. Frank No'e

Citations in the corpus

• Error bounds for kernel-based approximations of the Koopman operator (2023, background): “It is well known that k generates a so-called reproducing kernel Hilbert space (RKHS) [1, 7, 47] ( H , ⟨· , ·⟩ ) of continuous functions, such that for ψ ∈ H the reproducing property holds, where Φ : X → H denotes the so-called feature map corresponding to the kernel k , i.e., In the sequel, we…”
• Conformal prediction with conditional guarantees (2023, neutral): “Additional examples and background material on reproducing kernel Hilbert spaces can be found in Paulsen and Raghupathi (2016).”
• Multiplier algebras of complete Nevanlinna–Pick spaces: Dilations, boundary representations and hyperrigidity (2016, background): “Background material on reproducing kernel Hilbert spaces can be found in [42] and [4].”