Saved in:
| Main Authors: | Klus, Stefan, Bramburger, Jason J. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.18147 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Optimization of randomized neural networks for transfer operator approximation
by: Tabish, Mohammad, et al.
Published: (2026)
by: Tabish, Mohammad, et al.
Published: (2026)
Transfer operators on graphs: Spectral clustering and beyond
by: Klus, Stefan, et al.
Published: (2023)
by: Klus, Stefan, et al.
Published: (2023)
How deep is your network? Deep vs. shallow learning of transfer operators
by: Tabish, Mohammad, et al.
Published: (2025)
by: Tabish, Mohammad, et al.
Published: (2025)
Data-driven approximation of transfer operators for mean-field stochastic differential equations
by: Ioannou, Eirini, et al.
Published: (2025)
by: Ioannou, Eirini, et al.
Published: (2025)
Dynamical systems and complex networks: A Koopman operator perspective
by: Klus, Stefan, et al.
Published: (2024)
by: Klus, Stefan, et al.
Published: (2024)
Learning dynamical systems from data: Gradient-based dictionary optimization
by: Tabish, Mohammad, et al.
Published: (2024)
by: Tabish, Mohammad, et al.
Published: (2024)
Capturing the critical coupling of large random Kuramoto networks with graphons
by: Bramburger, Jason, et al.
Published: (2025)
by: Bramburger, Jason, et al.
Published: (2025)
Transferability of Graph Neural Networks using Graphon and Sampling Theories
by: Neuman, A. Martina, et al.
Published: (2023)
by: Neuman, A. Martina, et al.
Published: (2023)
Data-driven system identification using quadratic embeddings of nonlinear dynamics
by: Klus, Stefan, et al.
Published: (2025)
by: Klus, Stefan, et al.
Published: (2025)
A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs
by: Zhu, Hongyu, et al.
Published: (2022)
by: Zhu, Hongyu, et al.
Published: (2022)
On the lattice property of the Koopman operator spectrum
by: Bramburger, Jason J.
Published: (2025)
by: Bramburger, Jason J.
Published: (2025)
Bayesian Transfer Operators in Reproducing Kernel Hilbert Spaces
by: Boshoff, Septimus, et al.
Published: (2025)
by: Boshoff, Septimus, et al.
Published: (2025)
Clustering Time-Evolving Networks Using the Spatio-Temporal Graph Laplacian
by: Trower, Maia, et al.
Published: (2024)
by: Trower, Maia, et al.
Published: (2024)
Weighted Birkhoff Averages Accelerate Data-Driven Methods
by: Bou-Sakr-El-Tayar, Maria, et al.
Published: (2025)
by: Bou-Sakr-El-Tayar, Maria, et al.
Published: (2025)
Random walk based snapshot clustering for detecting community dynamics in temporal networks
by: Blašković, Filip, et al.
Published: (2024)
by: Blašković, Filip, et al.
Published: (2024)
Reconstruction of frequency-localized functions from pointwise samples via least squares and deep learning
by: Neuman, A. Martina, et al.
Published: (2025)
by: Neuman, A. Martina, et al.
Published: (2025)
Avoiding spectral pollution for transfer operators using residuals
by: Herwig, April, et al.
Published: (2025)
by: Herwig, April, et al.
Published: (2025)
Private graphon estimation via sum-of-squares
by: Chen, Hongjie, et al.
Published: (2024)
by: Chen, Hongjie, et al.
Published: (2024)
Pattern Formation in Random Networks Using Graphons
by: Bramburger, Jason, et al.
Published: (2021)
by: Bramburger, Jason, et al.
Published: (2021)
Quantifying uncertainty in spectral clusterings: expectations for perturbed and incomplete data
by: Dölz, Jürgen, et al.
Published: (2025)
by: Dölz, Jürgen, et al.
Published: (2025)
Random walks on simplicial complexes
by: Bonis, Thomas, et al.
Published: (2024)
by: Bonis, Thomas, et al.
Published: (2024)
Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning
by: Li, Xiang, et al.
Published: (2021)
by: Li, Xiang, et al.
Published: (2021)
LSEC: Large-scale spectral ensemble clustering
by: Li, Hongmin, et al.
Published: (2021)
by: Li, Hongmin, et al.
Published: (2021)
Advanced spectral clustering for heterogeneous data in credit risk monitoring systems
by: Han, Lu, et al.
Published: (2025)
by: Han, Lu, et al.
Published: (2025)
Bounding Escape Rates and Approximating Quasi-Stationary Distributions of Brownian Dynamics
by: Bramburger, Jason J.
Published: (2025)
by: Bramburger, Jason J.
Published: (2025)
Efficient Approximation of Molecular Kinetics using Random Fourier Features
by: Nüske, Feliks, et al.
Published: (2023)
by: Nüske, Feliks, et al.
Published: (2023)
On time series clustering with k-means
by: Holder, Christopher, et al.
Published: (2024)
by: Holder, Christopher, et al.
Published: (2024)
Stable spectral neural operator for learning stiff PDE systems from limited data
by: Zhang, Rui, et al.
Published: (2025)
by: Zhang, Rui, et al.
Published: (2025)
Random feature approximation for general spectral methods
by: Nguyen, Mike, et al.
Published: (2025)
by: Nguyen, Mike, et al.
Published: (2025)
Transformers for dynamical systems learn transfer operators in-context
by: Bao, Anthony, et al.
Published: (2026)
by: Bao, Anthony, et al.
Published: (2026)
On the Statistical Query Complexity of Learning Semiautomata: a Random Walk Approach
by: Giapitzakis, George, et al.
Published: (2025)
by: Giapitzakis, George, et al.
Published: (2025)
Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining
by: Ren, Yunwei, et al.
Published: (2026)
by: Ren, Yunwei, et al.
Published: (2026)
Randomly Pivoted Partial Cholesky: Random How?
by: Steinerberger, Stefan
Published: (2024)
by: Steinerberger, Stefan
Published: (2024)
Fast and explainable clustering in the Manhattan and Tanimoto distance
by: Güttel, Stefan, et al.
Published: (2026)
by: Güttel, Stefan, et al.
Published: (2026)
Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics
by: Gaitonde, Jason, et al.
Published: (2024)
by: Gaitonde, Jason, et al.
Published: (2024)
To transfer or not transfer: Unified transferability metric and analysis
by: Zhan, Qianshan, et al.
Published: (2023)
by: Zhan, Qianshan, et al.
Published: (2023)
Infinite hierarchical contrastive clustering for personal digital envirotyping
by: Huang, Ya-Yun, et al.
Published: (2025)
by: Huang, Ya-Yun, et al.
Published: (2025)
Machine Learning of polymer types from the spectral signature of Raman spectroscopy microplastics data
by: Ramanna, Sheela, et al.
Published: (2022)
by: Ramanna, Sheela, et al.
Published: (2022)
Revisiting Randomization in Greedy Model Search
by: Chen, Xin, et al.
Published: (2025)
by: Chen, Xin, et al.
Published: (2025)
Mitigating spectral bias for the multiscale operator learning
by: Liu, Xinliang, et al.
Published: (2022)
by: Liu, Xinliang, et al.
Published: (2022)
Similar Items
-
Optimization of randomized neural networks for transfer operator approximation
by: Tabish, Mohammad, et al.
Published: (2026) -
Transfer operators on graphs: Spectral clustering and beyond
by: Klus, Stefan, et al.
Published: (2023) -
How deep is your network? Deep vs. shallow learning of transfer operators
by: Tabish, Mohammad, et al.
Published: (2025) -
Data-driven approximation of transfer operators for mean-field stochastic differential equations
by: Ioannou, Eirini, et al.
Published: (2025) -
Dynamical systems and complex networks: A Koopman operator perspective
by: Klus, Stefan, et al.
Published: (2024)