Bayesian optimisation of functions on graphs
The increasing availability of graph-structured data motivates the task of optimising over functions defined on the node set of graphs. Traditional graph search algorithms can be applied in this case, but they may be sample-inefficient and do not make use of information about the function values; on...
Main Authors: | Wan, X, Osselin, P, Kenlay, H, Ru, B, Osborne, MA, Dong, X |
---|---|
Format: | Conference item |
Language: | English |
Published: |
Neural Information Processing Systems Foundation
2024
|
Similar Items
-
Adversarial attacks on graph classification via Bayesian optimisation
by: Wan, X, et al.
Published: (2021) -
Structure-aware robustness certificates for graph classification
by: Osselin, P, et al.
Published: (2023) -
Interpretable neural architecture search via Bayesian optimisation with Weisfeiler-Lehman kernels
by: Ru, B, et al.
Published: (2021) -
On the stability of polynomial spectral graph filters
by: Kenlay, H, et al.
Published: (2020) -
Interpretable stability bounds for spectral graph filters
by: Kenlay, H, et al.
Published: (2021)