Peter Bloem
Peter Bloem
Vrije Universiteit Amsterdam
Verified email at - Homepage
Cited by
Cited by
Modeling relational data with graph convolutional networks
M Schlichtkrull, TN Kipf, P Bloem, M Berg, R. vd, Titov, I., and Welling
European Semantic Web Conference, 593-607, 2018
The knowledge graph as the default data model for learning on heterogeneous knowledge
X Wilcke, P Bloem, V De Boer
Data Science 1 (1-2), 39-57, 2017
The MIDI linked data cloud
A Meroño-Peñuela, R Hoekstra, A Gangemi, P Bloem, R de Valk, ...
International Semantic Web Conference, 156-164, 2017
Machine learning on linked data, a position paper
P Bloem, GKD De Vries
Linked Data for Knowledge Discovery, 69, 2014
Are names meaningful? Quantifying social meaning on the semantic web
S de Rooij, W Beek, P Bloem, F van Harmelen, S Schlobach
International Semantic Web Conference, 184-199, 2016
Simplifying RDF Data for Graph-Based Machine Learning.
P Bloem, A Wibisono, G De Vries
KNOW@ LOD 1243, 2014
A safe approximation for Kolmogorov complexity
P Bloem, F Mota, S de Rooij, L Antunes, P Adriaans
International Conference on Algorithmic Learning Theory, 336-350, 2014
Large-scale network motif learning with compression
P Bloem, S de Rooij
CoRR arXiv 1701, 2017
Two problems for sophistication
P Bloem, S de Rooij, P Adriaans
International Conference on Algorithmic Learning Theory, 379-394, 2015
Generating scientific documentation for computational experiments using provenance
A Wibisono, P Bloem, GKD de Vries, P Groth, A Belloum, M Bubak
International Provenance and Annotation Workshop, 168-179, 2014
Deep Learning for Classification Tasks on Geospatial Vector Polygons
R van't Veer, P Bloem, E Folmer
arXiv, arXiv: 1806.03857, 2018
A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study
A El-Gazzar, M Quaak, L Cerliani, P Bloem, G van Wingen, RM Thomas
OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical …, 2019
Single sample statistics: exercises in learning from just one example
P Bloem
University of Amsterdam, 2016
End-to-End Learning from Complex Multigraphs with Latent Graph Convolutional Networks
F Hermsen, P Bloem, F Jansen, W Vos
arXiv preprint arXiv:1908.05365, 2019
Exploiting Temporality for Semi-Supervised Video Segmentation
R Sibechi, O Booij, N Baka, P Bloem
Proceedings of the IEEE International Conference on Computer Vision …, 2019
Three tools for practical differential privacy
KL van der Veen, R Seggers, P Bloem, G Patrini
arXiv preprint arXiv:1812.02890, 2018
A tutorial on MDL hypothesis testing for graph analysis
P Bloem, S de Rooij
arXiv preprint arXiv:1810.13163, 2018
Deep Learning for Classification Tasks on Geospatial Vector Polygons
R Veer, P Bloem, E Folmer
arXiv preprint arXiv:1806.03857, 2018
End-to-End Entity Classification on Multimodal Knowledge Graphs
WX Wilcke, P Bloem, V de Boer, RH van t Veer, FAH van Harmelen
arXiv, arXiv: 2003.12383, 2020
SUBMASSIVE: Resolving Subclass Cycles in Very Large Knowledge Graphs
S Wang, P Bloem, J Raad, F van Harmelen
Workshop on Large Scale RDF Analytics (LASCAR), 2020
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