Learning Transition Operators From Sparse Space-Time Samples-Reference-Cited by-同舟云学术

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Learning Transition Operators From Sparse Space-Time Samples

Published:2024-09 Issue:9 Volume:70 Page:6412-6446
ISSN:0018-9448
Container-title:IEEE Transactions on Information Theory
language:
Short-container-title:IEEE Trans. Inform. Theory

Author:

Kümmerle Christian¹^ORCID,Maggioni Mauro²,Tang Sui³^ORCID

Affiliation:

1. Department of Computer Science, The University of North Carolina at Charlotte, Charlotte, NC, USA

2. Department of Mathematics, Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA

3. Department of Mathematics, University of California at Santa Barbara, Isla Vista, Santa Barbara, CA, USA

Funder

Faculty Early Career Development Award sponsored by the University of California at Santa Barbara

Hellman Family Faculty Fellowship

NSF

Simons Fellowship

Air Force Office of Scientific Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/18/10642977/10558780-aam.pdf

Reference142 articles.

1. SEMI-BLIND INFERENCE OF TOPOLOGIES AND SIGNALS OVER GRAPHS

2. Characterization and Inference of Graph Diffusion Processes From Observations of Stationary Signals

3. Inference of Spatio-Temporal Functions Over Graphs via Multikernel Kriged Kalman Filtering

4. Learning Laplacian Matrix in Smooth Graph Signal Representations

5. Learning Heat Diffusion Graphs

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