
TUDataset: A collection of benchmark datasets for learning with graphs
Recently, there has been an increasing interest in (supervised) learning...
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Deep Graph Matching Consensus
This work presents a twostage neural architecture for learning and refi...
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Deep WeisfeilerLehman Assignment Kernels via Multiple Kernel Learning
Kernels for structured data are commonly obtained by decomposing objects...
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A Survey on Graph Kernels
Graph kernels have become an established and widelyused technique for s...
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Maximum Cut Parameterized by Crossing Number
Given an edgeweighted graph G on n nodes, the NPhard MaxCut problem a...
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Computing Optimal Assignments in Linear Time for Graph Matching
Finding an optimal assignment between two sets of objects is a fundament...
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FixedParameter Algorithms for the Weighted MaxCut Problem on Embedded 1Planar Graphs
We propose two fixedparameter tractable algorithms for the weighted Max...
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A note on blockandbridge preserving maximum common subgraph algorithms for outerplanar graphs
Schietgat, Ramon and Bruynooghe proposed a polynomialtime algorithm for...
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Largest Weight Common Subtree Embeddings with Distance Penalties
The largest common embeddable subtree problem asks for the largest possi...
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A FixedParameter Algorithm for the MaxCut Problem on Embedded 1Planar Graphs
We propose a fixedparameter tractable algorithm for the MaxCut problem...
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Recognizing Cuneiform Signs Using Graph Based Methods
The cuneiform script constitutes one of the earliest systems of writing ...
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A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels
Nonlinear kernel methods can be approximated by fast linear ones using ...
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Faster Kernels for Graphs with Continuous Attributes via Hashing
While stateoftheart kernels for graphs with discrete labels scale wel...
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On Valid Optimal Assignment Kernels and Applications to Graph Classification
The success of kernel methods has initiated the design of novel positive...
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Nils M. Kriege
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