
CGAL
 Referenced in 367 articles
[sw00118]
 objects and predicates are regrouped in CGAL Kernels. Finally, the Support Library offers geometric object ... libraries Qt, Geomview, and the Boost Graph Library...

graph2vec
 Referenced in 6 articles
[sw32340]
 naturally unequipped to learn such representations, graph kernels remain as the most effective ... obtaining them. However, these graph kernels use handcrafted features (e.g., shortest paths, graphlets ... datadriven distributed representations of arbitrary sized graphs. graph2vec’s embeddings are learnt ... competitive with stateoftheart graph kernels...

subgraph2vec
 Referenced in 4 articles
[sw36496]
 recent advancements in Deep Learning and Graph Kernels. These latent representations encode semantic substructure dependencies ... statistical models for tasks such as graph classification, clustering, link prediction and community detection. subgraph2vec ... deep learning variant of WeisfeilerLehman graph kernel. Our experiments on several benchmark and large ... significant improvements in accuracies over existing graph kernels on both supervised and unsupervised learning tasks...

GPUVerify
 Referenced in 10 articles
[sw11260]
 semantics for GPU kernels represented by arbitrary reducible control flow graphs and compare this semantics ... method that allows GPU kernels with arbitrary reducible control flow graphs to be verified ... open source and commercial GPU kernels. Among these kernels, 42 exhibit unstructured control flow which...

NetLSD
 Referenced in 4 articles
[sw32341]
 comparisons still rely on direct approaches, graph kernels, or representationbased methods, which ... that allows for straightforward comparisons of large graphs. NetLSD extracts a compact signature that inherits ... heat or wave kernel; thus, it hears the shape of a graph. Our evaluation...

kLog
 Referenced in 4 articles
[sw10403]
 programming, and deductive databases. Access by the kernel to the rich representation is mediated ... relational representation is first transformed into a graph  in particular, a grounded ... entity/relationship diagram. Subsequently, a choice of graph kernel defines the feature space. kLog supports mixed...

PyOP2
 Referenced in 14 articles
[sw14924]
 parallel executions of computational kernels on unstructured meshes or graphs...

graphkernels
 Referenced in 2 articles
[sw27018]
 package graphkernels: Graph Kernels. A fast C++ implementation for computing various graph kernels including ... baselines), and (4) the WeisfeilerLehman graph kernel (state...

GraKeL
 Referenced in 2 articles
[sw27017]
 GraKeL: A Graph Kernel Library in Python. The problem of accurately measuring the similarity between ... applications in a variety of disciplines. Graph kernels have recently emerged as a promising approach ... many kernels, each focusing on different structural aspects of graphs. Here, we present ... GraKeL, a library that unifies several graph kernels into a common framework. The library...

kProbLog
 Referenced in 1 article
[sw18492]
 kProbLog as a language for learning with kernels. kProbLog allows to elegantly specify systems ... encodings of stateoftheart graph kernels such as WeisfeilerLehman graph kernels, propagation ... kernels and an instance of Graph Invariant ... Kernels (GIKs), a recent framework for graph kernels with continuous attributes. The number of feature...

InfoGraph
 Referenced in 2 articles
[sw37754]
 community analysis in social networks. Traditional graph kernel based methods are simple, yet effective...

iScore
 Referenced in 1 article
[sw33181]
 iScore: A novel graph kernelbased function for scoring proteinprotein docking models. Results: Here ... terms with a score obtained using a graph representation of the protein–protein interfaces ... represents the first successful demonstration of graph kernels to protein interfaces for effective discrimination...

SyncSpecCnn
 Referenced in 5 articles
[sw26163]
 with images that are 2D grids, shape graphs are irregular and nonisomorphic data structures ... sharing by parameterizing kernels in the spectral domain spanned by graph laplacian eigenbases. Under this ... different graphs. Towards these goals, we introduce a spectral parameterization of dilated convolutional kernels...

VIKAASA
 Referenced in 2 articles
[sw08393]
 Application Capable of Computing and Graphing Viability Kernels for Simple Viability Problems. This manual introduces ... graphing capabilities of those packages to approximate, visualise and test viability kernels for viability problems...

BBMCW
 Referenced in 4 articles
[sw21469]
 their scale. One such example is correspondence graphs derived from data association problems ... algorithm is based on the bitparallel kernel used by the BBMC family of published ... BBMC bitparallel kernel in large sparse graphs. Moreover, BBMCW also improves on bound computation...

Edge
 Referenced in 1 article
[sw30261]
 Edge: an extensible graph editor. EDGE is an editor kernel ... direct and visual manipulation of graphs. The kernel can be adapted quickly to diverse applications ... abstraction: how can users deal with large graphs containing hundreds of nodes and edges ... kernel be structured to be adaptable to various applications? EDGE uses a special graph representation...

KeLP
 Referenced in 3 articles
[sw26682]
 strings, trees or graphs and their combination with standard vectorial kernels. Additionally, it provides several...

TUDataset
 Referenced in 1 article
[sw37862]
 address this, we introduce the TUDataset for graph classification and regression. The collection consists ... provide Pythonbased data loaders, kernel and graph neural network baseline implementations, and evaluation tools...

COCONUT
 Referenced in 38 articles
[sw04760]
 global optimization problems with an opensource kernel, which can be expanded by commercial ... internal representation of various matrix classes. The graphs are implemented using the VGTL (Vienna Graph...