TMTSP-L1.3
A Spectral Framework for Graph Neural Operators: Convergence Guarantees and Tradeoffs
Roxanne Holden, Luana Ruiz, Johns Hopkins University, United States
Session:
Graphs and Networks Lecture
Track:
9: TMTSP - Theoretical and Methodological Trends in Signal Processing
Location:
Studio 1
Session Time:
Tue, 1 Sep, 10:50 - 12:30
Presentation Time:
Tue, 1 Sep, 11:30 - 11:50
Session Chair:
Petar Djuric, Stony Brook University
Presentation
Discussion
Session TMTSP-L1
TMTSP-L1.1: NONSTATIONARY GRAPH FILTERS BASED ON LOCALIZED FRAMES
Philipp Reingruber, Gerald Matz, Technische Universität Wien, Austria
TMTSP-L1.2: ORTHOGONAL L1 FOURIER TRANSFORM FOR DIGRAPHS
Vedran Mihal, Markus Püschel, ETH Zurich, Switzerland
TMTSP-L1.3: A Spectral Framework for Graph Neural Operators: Convergence Guarantees and Tradeoffs
Roxanne Holden, Luana Ruiz, Johns Hopkins University, United States
TMTSP-L1.4: EFFICIENT SPECTRAL EMBEDDINGS OF GRAPH EDGES
Abdullah Karaaslanli, Mohammad Eini, Panagiotis A. Traganitis, Michigan State University, United States; Vasileios Kalantzis, IBM Research, United States
TMTSP-L1.5: Blockwise Sparsification with Error Feedback for Communication-Efficient Federated Learning
Dawit Kiros Redie, Norwegian University of Science and Technology(NTNU), Norway; Reza Arablouei, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia; Stefan Werner, Norwegian University of Science and Technology(NTNU), Norway
Resources
No resources available.