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Singular Value Decomposition of Operators on Reproducing Kernel Hilbert
  Spaces
v1v2 (latest)

Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces

24 July 2018
Mattes Mollenhauer
Ingmar Schuster
Stefan Klus
Christof Schütte
ArXiv (abs)PDFHTML

Papers citing "Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces"

15 / 15 papers shown
Title
Deep spatio-temporal point processes: Advances and new directions
Deep spatio-temporal point processes: Advances and new directions
Xiuyuan Cheng
Zheng Dong
Yao Xie
AI4TS
78
0
0
08 Apr 2025
Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators
Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators
Naichang Ke
Ryogo Tanaka
Yoshinobu Kawahara
90
0
0
06 Jan 2025
Variational Search Distributions
Variational Search Distributions
Daniel M. Steinberg
Rafael Oliveira
Cheng Soon Ong
Edwin V. Bonilla
114
1
0
10 Sep 2024
Dynamical systems and complex networks: A Koopman operator perspective
Dynamical systems and complex networks: A Koopman operator perspective
Stefan Klus
Natavsa Djurdjevac Conrad
51
3
0
14 May 2024
A randomized algorithm to solve reduced rank operator regression
A randomized algorithm to solve reduced rank operator regression
G. Turri
Vladimir Kostic
P. Novelli
Massimiliano Pontil
103
4
0
28 Dec 2023
Deep graph kernel point processes
Deep graph kernel point processes
Zheng Dong
Matthew Repasky
Xiuyuan Cheng
Yao Xie
3DPC
100
3
0
20 Jun 2023
Estimating Koopman operators with sketching to provably learn large
  scale dynamical systems
Estimating Koopman operators with sketching to provably learn large scale dynamical systems
Giacomo Meanti
Antoine Chatalic
Vladimir Kostic
P. Novelli
Massimiliano Pontil
Lorenzo Rosasco
92
11
0
07 Jun 2023
Spatio-temporal point processes with deep non-stationary kernels
Spatio-temporal point processes with deep non-stationary kernels
Zheng Dong
Xiuyuan Cheng
Yao Xie
BDLAI4TS
81
10
0
21 Nov 2022
Learning Transfer Operators by Kernel Density Estimation
Learning Transfer Operators by Kernel Density Estimation
Sudam Surasinghe
Jeremie Fish
Erik Bollt
18
2
0
01 Aug 2022
Learning Dynamical Systems via Koopman Operator Regression in
  Reproducing Kernel Hilbert Spaces
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces
Vladimir Kostic
P. Novelli
Andreas Maurer
C. Ciliberto
Lorenzo Rosasco
Massimiliano Pontil
78
62
0
27 May 2022
Symmetric and antisymmetric kernels for machine learning problems in
  quantum physics and chemistry
Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry
Stefan Klus
Patrick Gelß
Feliks Nuske
Frank Noé
47
21
0
31 Mar 2021
Nonparametric approximation of conditional expectation operators
Nonparametric approximation of conditional expectation operators
Mattes Mollenhauer
P. Koltai
95
17
0
23 Dec 2020
A Rigorous Theory of Conditional Mean Embeddings
A Rigorous Theory of Conditional Mean Embeddings
I. Klebanov
Ingmar Schuster
T. Sullivan
89
41
0
02 Dec 2019
Kernel methods for detecting coherent structures in dynamical data
Kernel methods for detecting coherent structures in dynamical data
Stefan Klus
B. Husic
Mattes Mollenhauer
Frank Noé
57
29
0
16 Apr 2019
A kernel-based approach to molecular conformation analysis
A kernel-based approach to molecular conformation analysis
Stefan Klus
A. Bittracher
Ingmar Schuster
Christof Schütte
59
26
0
28 Sep 2018
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