Peter Bloem

According to our database, Peter Bloem authored at least 45 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

SUBMASSIVE: Resolving Subclass Cycles in Very Large Knowledge Graphs.

Shuai Wang, Peter Bloem, Joe Raad, Frank van Harmelen

CoRR, 2024

Truth-value judgment in language models: belief directions are context sensitive.

Stefan F. Schouten, Peter Bloem, Ilia Markov, Piek Vossen

CoRR, 2024

Probing LLMs for Logical Reasoning.

Francesco Manigrasso, Stefan F. Schouten, Lia Morra, Peter Bloem

Proceedings of the Neural-Symbolic Learning and Reasoning - 18th International Conference, 2024

ReWise: A Relation-Wise Sampling Framework for Relational Graph Convolutional Networks.

Taraneh Younesian, Peter Bloem, Stefan Schlobach

Proceedings of the Knowledge Graphs in the Age of Language Models and Neuro-Symbolic AI, 2024

2023

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation.

Thiviyan Thanapalasingam, Emile van Krieken, Peter Bloem, Paul Groth

Dataset, April, 2023

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation.

Thiviyan Thanapalasingam, Emile van Krieken, Peter Bloem, Paul Groth

Dataset, April, 2023

Refining Large Integrated Identity Graphs using the Unique Name Assumption.

Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen

Dataset, March, 2023

Refining Large Integrated Identity Graphs using the Unique Name Assumption.

Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen

Dataset, March, 2023

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks.

Taraneh Younesian, Thiviyan Thanapalasingam, Emile van Krieken, Daniel Daza, Peter Bloem

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

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation.

Thiviyan Thanapalasingam, Emile van Krieken, Peter Bloem, Paul Groth

CoRR, 2023

Refining Large Integrated Identity Graphs Using the Unique Name Assumption.

Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen

Proceedings of the Semantic Web - 20th International Conference, 2023

Reasoning about Ambiguous Definite Descriptions.

Stefan F. Schouten, Peter Bloem, Ilia Markov, Piek Vossen

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Graphs of redirection: an examination of URIs in identity graphs.

Shuai Wang, Idries Nasim, Joe Raad, Peter Bloem, Frank van Harmelen

Dataset, October, 2022

Relational graph convolutional networks: a closer look.

Thiviyan Thanapalasingam, Lucas van Berkel, Peter Bloem, Paul Groth

PeerJ Comput. Sci., 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

What does it mean when your URIs are redirected? Examining identity and redirection in the LOD cloud.

Idries Nasim, Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen

Proceedings of the 8th Workshop on Managing the Evolution and Preservation of the Data Web (MEPDaW) co-located with the 21st International Semantic Web Conference (ISWC 2022), 2022

Probing the representations of named entities in Transformer-based Language Models.

Stefan F. Schouten, Peter Bloem, Piek Vossen

Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022

2021

Annotated (Pseudo-)Transitive Relations of the LOD Cloud.

Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen

Dataset, March, 2021

Finding Motifs in Knowledge Graphs using Compression.

Peter Bloem

CoRR, 2021

Refining Transitive and Pseudo-Transitive Relations at Web Scale.

Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen

Proceedings of the Semantic Web - 18th International Conference, 2021

kgbench: A Collection of Knowledge Graph Datasets for Evaluating Relational and Multimodal Machine Learning.

Peter Bloem, Xander Wilcke, Lucas van Berkel, Victor de Boer

Proceedings of the Semantic Web - 18th International Conference, 2021

2020

Annotated Pseudo-Transitive Relations of the LOD Cloud.

Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen

Dataset, December, 2020

Large-scale network motif analysis using compression.

Peter Bloem, Steven de Rooij

Data Min. Knowl. Discov., 2020

Uncertainty Intervals for Graph-based Spatio-Temporal Traffic Prediction.

Tijs Maas, Peter Bloem

CoRR, 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

Evaluating the Robustness of Question-Answering Models to Paraphrased Questions.

Paulo Alting von Geusau, Peter Bloem

Proceedings of the Artificial Intelligence and Machine Learning - 32nd Benelux Conference, 2020

2019

End-to-End Learning from Complex Multigraphs with Latent Graph Convolutional Networks.

Floris Hermsen, Peter Bloem, Fabian Jansen, Wolf Vos

CoRR, 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

Proceedings of the OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, 2019

Exploiting Temporality for Semi-Supervised Video Segmentation.

Radu Sibechi, Olaf Booij, Nora Baka, Peter Bloem

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018

Three Tools for Practical Differential Privacy.

Koen Lennart van der Veen, Ruben Seggers, Peter Bloem, Giorgio Patrini

CoRR, 2018

A tutorial on MDL hypothesis testing for graph analysis.

Peter Bloem, Steven de Rooij

CoRR, 2018

Learning sparse transformations through backpropagation.

Peter Bloem

CoRR, 2018

Deep Learning for Classification Tasks on Geospatial Vector Polygons.

Rein van 't Veer, Peter Bloem, Erwin Folmer

CoRR, 2018

Modeling Relational Data with Graph Convolutional Networks.

Michael Sejr Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, Max Welling

Proceedings of the Semantic Web - 15th International Conference, 2018

2017

The knowledge graph as the default data model for learning on heterogeneous knowledge.

Xander Wilcke, Peter Bloem, Victor de Boer

Data Sci., 2017

An Expectation-Maximization Algorithm for the Fractal Inverse Problem.

Peter Bloem, Steven de Rooij

CoRR, 2017

Large-Scale Network Motif Learning with Compression.

Peter Bloem, Steven de Rooij

CoRR, 2017

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

Proceedings of the Semantic Web - ISWC 2017, 2017

2016

Are Names Meaningful? Quantifying Social Meaning on the Semantic Web.

Steven de Rooij, Wouter Beek, Peter Bloem, Frank van Harmelen, Stefan Schlobach

Proceedings of the Semantic Web - ISWC 2016, 2016

2015

Two Problems for Sophistication.

Peter Bloem, Steven de Rooij, Pieter Adriaans

Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

2014

Machine Learning on Linked Data, a Position Paper.

Peter Bloem, Gerben de Vries

Proceedings of the 1st Workshop on Linked Data for Knowledge Discovery co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), 2014

Generating Scientific Documentation for Computational Experiments Using Provenance.

Adianto Wibisono, Peter Bloem, Gerben Klaas Dirk de Vries, Paul Groth, Adam Belloum, Marian Bubak

Proceedings of the Provenance and Annotation of Data and Processes, 2014

Simplifying RDF Data for Graph-Based Machine Learning.

Peter Bloem, Adianto Wibisono, Gerben de Vries

Proceedings of the 3rd Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data co-located with 11th Extended Semantic Web Conference (ESWC 2014), 2014

A Safe Approximation for Kolmogorov Complexity.

Peter Bloem, Francisco Mota, Steven de Rooij, Luis Antunes, Pieter Adriaans

Proceedings of the Algorithmic Learning Theory - 25th International Conference, 2014