A Safe Approximation for Kolmogorov Complexity. - Peter Bloem; Francisco Mota; Steven de Rooij; Luis Antunes 002; Pieter Adriaans (ALT, 2014)

Simplifying RDF Data for Graph-Based Machine Learning. - Peter Bloem; Adianto Wibisono; Gerben de Vries (KNOW@LOD, 2014)

Generating Scientific Documentation for Computational Experiments Using Provenance. - Adianto Wibisono; Peter Bloem; Gerben Klaas Dirk de Vries; Paul Groth; Adam Belloum; Marian Bubak (IPAW, 2014)

Machine Learning on Linked Data, a Position Paper. - Peter Bloem; Gerben de Vries (LD4KD, 2014)

Two Problems for Sophistication. - Peter Bloem; Steven de Rooij; Pieter Adriaans (ALT, 2015)

Are Names Meaningful? Quantifying Social Meaning on the Semantic Web. - Steven de Rooij; Wouter Beek; Peter Bloem; Frank van Harmelen; Stefan Schlobach (ISWC (1), 2016)

The MIDI Linked Data Cloud. - Albert Meroño-Peñuela; Rinke Hoekstra; Aldo Gangemi; Peter Bloem; Reinier de Valk; Bas Stringer; Berit Janssen; Victor de Boer; Alo Allik; Stefan Schlobach; Kevin R. Page (ISWC (2), 2017)

Large-Scale Network Motif Learning with Compression. - Peter Bloem; Steven de Rooij (CoRR, 2017)

An Expectation-Maximization Algorithm for the Fractal Inverse Problem. - Peter Bloem; Steven de Rooij (CoRR, 2017)

The knowledge graph as the default data model for learning on heterogeneous knowledge. - Xander Wilcke; Peter Bloem; Victor de Boer (Data Sci., 2017)

Modeling Relational Data with Graph Convolutional Networks. - Michael Sejr Schlichtkrull; Thomas N. Kipf; Peter Bloem; Rianne van den Berg; Ivan Titov 001; Max Welling (ESWC, 2018)

Deep Learning for Classification Tasks on Geospatial Vector Polygons. - Rein van 't Veer; Peter Bloem; Erwin Folmer (CoRR, 2018)

Learning sparse transformations through backpropagation. - Peter Bloem (CoRR, 2018)

A tutorial on MDL hypothesis testing for graph analysis. - Peter Bloem; Steven de Rooij (CoRR, 2018)

Three Tools for Practical Differential Privacy. - Koen Lennart van der Veen; Ruben Seggers; Peter Bloem; Giorgio Patrini (CoRR, 2018)

Exploiting Temporality for Semi-Supervised Video Segmentation. - Radu Sibechi; Olaf Booij; Nora Baka; Peter Bloem (ICCV Workshops, 2019)

A Hybrid 3DCNN and 3DC-LSTM Based Model for 4D Spatio-Temporal fMRI Data: An ABIDE Autism Classification Study. - Ahmed El Gazzar; Mirjam Quaak; Leonardo Cerliani; Peter Bloem; Guido van Wingen; Rajat Mani Thomas (OR/MLCN@MICCAI, 2019)

End-to-End Learning from Complex Multigraphs with Latent Graph Convolutional Networks. - Floris Hermsen; Peter Bloem; Fabian Jansen; Wolf Vos (CoRR, 2019)

Evaluating the Robustness of Question-Answering Models to Paraphrased Questions. - Paulo Alting von Geusau; Peter Bloem (BNAIC/BENELEARN (Selected Papers), 2020)

End-to-End Entity Classification on Multimodal Knowledge Graphs. - W. X. Wilcke; Peter Bloem; Victor de Boer; R. H. van t Veer; F. A. H. van Harmelen (CoRR, 2020)

Uncertainty Intervals for Graph-based Spatio-Temporal Traffic Prediction. - Tijs Maas; Peter Bloem (CoRR, 2020)

Large-scale network motif analysis using compression. - Peter Bloem; Steven de Rooij (Data Min. Knowl. Discov., 2020)

Annotated Pseudo-Transitive Relations of the LOD Cloud. - Shuai Wang 014; Joe Raad; Peter Bloem; Frank van Harmelen (Zenodo, 2020)

kgbench: A Collection of Knowledge Graph Datasets for Evaluating Relational and Multimodal Machine Learning. - Peter Bloem; Xander Wilcke; Lucas van Berkel; Victor de Boer (ESWC, 2021)

Refining Transitive and Pseudo-Transitive Relations at Web Scale. - Shuai Wang 014; Joe Raad; Peter Bloem; Frank van Harmelen (ESWC, 2021)

Finding Motifs in Knowledge Graphs using Compression. - Peter Bloem (CoRR, 2021)

Annotated (Pseudo-)Transitive Relations of the LOD Cloud. - Shuai Wang 014; Joe Raad; Peter Bloem; Frank van Harmelen (Zenodo, 2021)

Probing the representations of named entities in Transformer-based Language Models. - Stefan F. Schouten; Peter Bloem; Piek Vossen (BlackboxNLP@EMNLP, 2022)

What does it mean when your URIs are redirected? Examining identity and redirection in the LOD cloud. - Idries Nasim; Shuai Wang 014; Joe Raad; Peter Bloem; Frank van Harmelen (MEPDaW@ISWC, 2022)

Robin's Viewer: Using deep-learning predictions to assist EEG annotation. - Robin Weiler; Marina Diachenko; Erika L. Juarez-Martinez; Arthur Ervin Avramiea; Peter Bloem; Klaus Linkenkaer-Hansen (Frontiers Neuroinformatics, 2022)

Relational graph convolutional networks: a closer look. - Thiviyan Thanapalasingam; Lucas van Berkel; Peter Bloem; Paul Groth (PeerJ Comput. Sci., 2022)

Graphs of redirection: an examination of URIs in identity graphs. - Shuai Wang 014; Idries Nasim; Joe Raad; Peter Bloem; Frank van Harmelen (Zenodo, 2022)

Reasoning about Ambiguous Definite Descriptions. - Stefan F. Schouten; Peter Bloem; Ilia Markov; Piek Vossen (EMNLP (Findings), 2023)

Refining Large Integrated Identity Graphs Using the Unique Name Assumption. - Shuai Wang 014; Joe Raad; Peter Bloem; Frank van Harmelen (ESWC, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (CoRR, 2023)

End-to-End Learning on Multimodal Knowledge Graphs. - W. X. Wilcke; Peter Bloem; Victor de Boer; R. H. van t Veer (CoRR, 2023)

Refining Large Integrated Identity Graphs using the Unique Name Assumption. - Shuai Wang 014; Joe Raad; Peter Bloem; Frank van Harmelen (Zenodo, 2023)

Refining Large Integrated Identity Graphs using the Unique Name Assumption. - Shuai Wang 014; Joe Raad; Peter Bloem; Frank van Harmelen (Zenodo, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (Zenodo, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (Zenodo, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (Zenodo, 2023)

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. - Thiviyan Thanapalasingam; Emile van Krieken; Peter Bloem; Paul Groth (Zenodo, 2023)

ReWise: A Relation-Wise Sampling Framework for Relational Graph Convolutional Networks. - Taraneh Younesian; Peter Bloem; Stefan Schlobach (SEMANTICS, 2024)

Probing LLMs for Logical Reasoning. - Francesco Manigrasso; Stefan F. Schouten; Lia Morra; Peter Bloem (NeSy (1), 2024)

Truth-value judgment in language models: belief directions are context sensitive. - Stefan F. Schouten; Peter Bloem; Ilia Markov; Piek Vossen (CoRR, 2024)

SUBMASSIVE: Resolving Subclass Cycles in Very Large Knowledge Graphs. - Shuai Wang 014; Peter Bloem; Joe Raad; Frank van Harmelen (CoRR, 2024)

SUBMASSIVE: Resolving Subclass Cycles in Very Large Knowledge Graphs. - Shuai Wang 014; Frank van Harmelen; Joe Raad; Peter Bloem (Zenodo, 2024)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks. - Taraneh Younesian; Daniel Daza; Emile van Krieken; Thiviyan Thanapalasingam; Peter Bloem (Trans. Mach. Learn. Res., 2025)

Universal pre-training by iterated random computation. - Peter Bloem (CoRR, 2025)