We initiate an open-source library for the efficient analysis of tempora...
We introduce the temporal graphlet kernel for classifying
dissemination ...
The vertex coloring problem asks for the minimum number of colors that c...
We apply state-of-the-art computational geometry methods to the problem ...
We propose the Temporal Walk Centrality, which quantifies the importance...
A typical task in temporal graphs analysis is answering
single-source-al...
We study the problem of finding the k most similar trajectories to a giv...
Recently, there has been an increasing interest in (supervised) learning...
Quantum annealing is getting increasing attention in combinatorial
optim...
The k-dimensional Weisfeiler-Leman algorithm is a well-known heuristic f...
Given an edge-weighted graph G on n nodes, the NP-hard Max-Cut problem a...
We discuss the complexity of path enumeration in weighted temporal graph...
We propose two fixed-parameter tractable algorithms for the weighted Max...
The Steiner tree problem with revenues, budgets and hop constraints (STP...
We consider the coordinate assignment phase of the well known Sugiyama
f...
Schietgat, Ramon and Bruynooghe proposed a polynomial-time algorithm for...
The Harary-Hill Conjecture states that for n≥ 3 every drawing of K_n
has...
The Harary-Hill Conjecture states that for n≥ 3 every drawing of K_n
has...
The largest common embeddable subtree problem asks for the largest possi...
We propose a fixed-parameter tractable algorithm for the Max-Cut
problem...
The Harary-Hill conjecture states that for every n>0 the complete graph ...
The cuneiform script constitutes one of the earliest systems of writing ...
The complexity of the maximum common connected subgraph problem in parti...
The vertex coloring problem asks for the minimum number of colors that c...
Most state-of-the-art graph kernels only take local graph properties int...
Non-linear kernel methods can be approximated by fast linear ones using
...
While state-of-the-art kernels for graphs with discrete labels scale wel...
We present a structural clustering algorithm for large-scale datasets of...
We propose graph kernels based on subgraph matchings, i.e.
structure-pre...