What is recorded here?
Parameterized graph filters as truncated Chebyshev polynomials of the Laplacian, evaluating them by sparse recurrence and combining graph coarsening with efficient pooling.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Inherits polynomial graph signal processing and spectral CNNs. Filtering costs scale with polynomial order and graph edges, not constant cost on arbitrary dense graphs; full layer costs include feature channels.
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People and systems
Michaël Defferrard; Xavier Bresson; Pierre Vandergheynst
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
ChebNet: localized polynomial graph filtering without eigendecomposition
Parameterized graph filters as truncated Chebyshev polynomials of the Laplacian, evaluating them by sparse recurrence and combining graph coarsening with efficient pooling.
Scientific scope
Inherits polynomial graph signal processing and spectral CNNs. Filtering costs scale with polynomial order and graph edges, not constant cost on arbitrary dense graphs; full layer costs include feature channels.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Michaël Defferrard; Xavier Bresson; Pierre Vandergheynst
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.