Search Results for author: Petra Mutzel

Found 12 papers, 6 papers with code

SAT Encoding of Partial Ordering Models for Graph Coloring Problems

1 code implementation23 Mar 2024 Daniel Faber, Adalat Jabrayilov, Petra Mutzel

For the widely studied GCP, we experimentally compare our new SAT encoding to the state-of-the-art approaches on the DIMACS benchmark set.

A Temporal Graphlet Kernel for Classifying Dissemination in Evolving Networks

1 code implementation12 Sep 2022 Lutz Oettershagen, Nils M. Kriege, Claude Jordan, Petra Mutzel

We introduce the \emph{temporal graphlet kernel} for classifying dissemination processes in labeled temporal graphs.

Temporal Walk Centrality: Ranking Nodes in Evolving Networks

1 code implementation8 Feb 2022 Lutz Oettershagen, Petra Mutzel, Nils M. Kriege

We propose the Temporal Walk Centrality, which quantifies the importance of a node by measuring its ability to obtain and distribute information in a temporal network.

Temporal Graph Kernels for Classifying Dissemination Processes

no code implementations14 Oct 2019 Lutz Oettershagen, Nils M. Kriege, Christopher Morris, Petra Mutzel

Hence, we confirm that taking temporal information into account is crucial for the successful classification of dissemination processes.

General Classification Graph Classification

Recognizing Cuneiform Signs Using Graph Based Methods

no code implementations16 Feb 2018 Nils M. Kriege, Matthias Fey, Denis Fisseler, Petra Mutzel, Frank Weichert

To this end, the distance measure is used to implement a nearest neighbor classifier leading to a high computational cost for the prediction phase with increasing training set size.

Global Weisfeiler-Lehman Graph Kernels

1 code implementation7 Mar 2017 Christopher Morris, Kristian Kersting, Petra Mutzel

Specifically, we introduce a novel graph kernel based on the $k$-dimensional Weisfeiler-Lehman algorithm.

General Classification Graph Classification

A Unifying View of Explicit and Implicit Feature Maps of Graph Kernels

no code implementations2 Mar 2017 Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel

On this basis we propose exact and approximative feature maps for widely used graph kernels based on the kernel trick.

Faster Kernels for Graphs with Continuous Attributes via Hashing

no code implementations1 Oct 2016 Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel

While state-of-the-art kernels for graphs with discrete labels scale well to graphs with thousands of nodes, the few existing kernels for graphs with continuous attributes, unfortunately, do not scale well.

StruClus: Structural Clustering of Large-Scale Graph Databases

no code implementations28 Sep 2016 Till Schäfer, Petra Mutzel

We present a structural clustering algorithm for large-scale datasets of small labeled graphs, utilizing a frequent subgraph sampling strategy.

Clustering

Subgraph Matching Kernels for Attributed Graphs

no code implementations27 Jun 2012 Nils Kriege, Petra Mutzel

To compute the kernel we propose a graph-theoretical algorithm inspired by a classical relation between common subgraphs of two graphs and cliques in their product graph observed by Levi (1973).

General Classification

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