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2020 – today
- 2024
[c19]Taraneh Younesian
, Peter Bloem, Stefan Schlobach:
ReWise: A Relation-Wise Sampling Framework for Relational Graph Convolutional Networks. SEMANTICS 2024: 123-141- [c18]Francesco Manigrasso, Stefan F. Schouten, Lia Morra, Peter Bloem:
Probing LLMs for Logical Reasoning. NeSy (1) 2024: 257-278 - [i19]Stefan F. Schouten, Peter Bloem, Ilia Markov, Piek Vossen:
Truth-value judgment in language models: belief directions are context sensitive. CoRR abs/2404.18865 (2024) - 2023
- [c17]Stefan F. Schouten, Peter Bloem, Ilia Markov, Piek Vossen:
Reasoning about Ambiguous Definite Descriptions. EMNLP (Findings) 2023: 4479-4484 - [c16]Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen:
Refining Large Integrated Identity Graphs Using the Unique Name Assumption. ESWC 2023: 55-71 - [d7]Thiviyan Thanapalasingam, Emile van Krieken, Peter Bloem, Paul Groth:
IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. Zenodo, 2023
- [d6]Thiviyan Thanapalasingam, Emile van Krieken, Peter Bloem, Paul Groth:
IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. Zenodo, 2023 - [d5]Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen:
Refining Large Integrated Identity Graphs using the Unique Name Assumption. Version 1. Zenodo, 2023 [all versions] - [d4]Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen:
Refining Large Integrated Identity Graphs using the Unique Name Assumption. Version 2. Zenodo, 2023 [all versions] - [i18]Thiviyan Thanapalasingam, Emile van Krieken, Peter Bloem, Paul Groth:
IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. CoRR abs/2307.06698 (2023) - [i17]W. X. Wilcke, Peter Bloem, Victor de Boer, R. H. van t Veer:
End-to-End Learning on Multimodal Knowledge Graphs. CoRR abs/2309.01169 (2023) - [i16]Taraneh Younesian, Thiviyan Thanapalasingam, Emile van Krieken, Daniel Daza, Peter Bloem:
GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks. CoRR abs/2310.03399 (2023) - [i15]Stefan F. Schouten, Peter Bloem, Ilia Markov, Piek Vossen:
Reasoning about Ambiguous Definite Descriptions. CoRR abs/2310.14657 (2023) - 2022
- [j4]Robin Weiler, Marina Diachenko, Erika L. Juarez-Martinez, Arthur Ervin Avramiea, Peter Bloem, Klaus Linkenkaer-Hansen:
Robin's Viewer: Using deep-learning predictions to assist EEG annotation. Frontiers Neuroinformatics 16 (2022) - [j3]Thiviyan Thanapalasingam, Lucas van Berkel, Peter Bloem, Paul Groth:
Relational graph convolutional networks: a closer look. PeerJ Comput. Sci. 8: e1073 (2022) - [c15]Stefan F. Schouten, Peter Bloem, Piek Vossen:
Probing the representations of named entities in Transformer-based Language Models. BlackboxNLP@EMNLP 2022: 384-393 - [c14]Idries Nasim, Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen:
What does it mean when your URIs are redirected? Examining identity and redirection in the LOD cloud. MEPDaW@ISWC 2022: 36-45 - [d3]Shuai Wang, Idries Nasim, Joe Raad, Peter Bloem, Frank van Harmelen:
Graphs of redirection: an examination of URIs in identity graphs. Zenodo, 2022 - 2021
- [c13]Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen:
Refining Transitive and Pseudo-Transitive Relations at Web Scale. ESWC 2021: 249-264 - [c12]Peter Bloem, Xander Wilcke, Lucas van Berkel, Victor de Boer:
kgbench: A Collection of Knowledge Graph Datasets for Evaluating Relational and Multimodal Machine Learning. ESWC 2021: 614-630 - [d2]Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen:
Annotated (Pseudo-)Transitive Relations of the LOD Cloud. Zenodo, 2021 - [i14]Peter Bloem:
Finding Motifs in Knowledge Graphs using Compression. CoRR abs/2104.08163 (2021) - [i13]Thiviyan Thanapalasingam, Lucas van Berkel, Peter Bloem, Paul Groth:
Relational Graph Convolutional Networks: A Closer Look. CoRR abs/2107.10015 (2021) - 2020
- [j2]Peter Bloem, Steven de Rooij:
Large-scale network motif analysis using compression. Data Min. Knowl. Discov. 34(5): 1421-1453 (2020) - [c11]Paulo Alting von Geusau, Peter Bloem:
Evaluating the Robustness of Question-Answering Models to Paraphrased Questions. BNAIC/BENELEARN (Selected Papers) 2020: 1-14 - [d1]Shuai Wang, Joe Raad, Peter Bloem, Frank van Harmelen:
Annotated Pseudo-Transitive Relations of the LOD Cloud. Zenodo, 2020 - [i12]Ahmed El Gazzar, Mirjam Quaak, Leonardo Cerliani, Peter Bloem, Guido van Wingen, Rajat Mani Thomas:
A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study. CoRR abs/2002.05981 (2020) - [i11]W. X. Wilcke, Peter Bloem, Victor de Boer, R. H. van t Veer, F. A. H. van Harmelen:
End-to-End Entity Classification on Multimodal Knowledge Graphs. CoRR abs/2003.12383 (2020) - [i10]Tijs Maas, Peter Bloem:
Uncertainty Intervals for Graph-based Spatio-Temporal Traffic Prediction. CoRR abs/2012.05207 (2020)
2010 – 2019
- 2019
- [c10]Radu Sibechi, Olaf Booij, Nora Baka, Peter Bloem:
Exploiting Temporality for Semi-Supervised Video Segmentation. ICCV Workshops 2019: 933-941 - [c9]Ahmed El Gazzar, Mirjam Quaak, Leonardo Cerliani, Peter Bloem, Guido van Wingen, Rajat Mani Thomas:
A Hybrid 3DCNN and 3DC-LSTM Based Model for 4D Spatio-Temporal fMRI Data: An ABIDE Autism Classification Study. OR/MLCN@MICCAI 2019: 95-102 - [i9]Floris Hermsen, Peter Bloem, Fabian Jansen, Wolf Vos:
End-to-End Learning from Complex Multigraphs with Latent Graph Convolutional Networks. CoRR abs/1908.05365 (2019) - [i8]Radu Sibechi, Olaf Booij, Nora Baka, Peter Bloem:
Exploiting Temporality for Semi-Supervised Video Segmentation. CoRR abs/1908.11309 (2019) - 2018
- [c8]Michael Sejr Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, Max Welling:
Modeling Relational Data with Graph Convolutional Networks. ESWC 2018: 593-607 - [i7]Rein van 't Veer, Peter Bloem, Erwin Folmer:
Deep Learning for Classification Tasks on Geospatial Vector Polygons. CoRR abs/1806.03857 (2018) - [i6]Peter Bloem:
Learning sparse transformations through backpropagation. CoRR abs/1810.09184 (2018) - [i5]Peter Bloem, Steven de Rooij:
A tutorial on MDL hypothesis testing for graph analysis. CoRR abs/1810.13163 (2018) - [i4]Koen Lennart van der Veen, Ruben Seggers, Peter Bloem, Giorgio Patrini:
Three Tools for Practical Differential Privacy. CoRR abs/1812.02890 (2018) - 2017
- [j1]Xander Wilcke, Peter Bloem, Victor de Boer:
The knowledge graph as the default data model for learning on heterogeneous knowledge. Data Sci. 1(1-2): 39-57 (2017) - [c7]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:
The MIDI Linked Data Cloud. ISWC (2) 2017: 156-164 - [i3]Peter Bloem, Steven de Rooij:
Large-Scale Network Motif Learning with Compression. CoRR abs/1701.02026 (2017) - [i2]Michael Sejr Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, Max Welling:
Modeling Relational Data with Graph Convolutional Networks. CoRR abs/1703.06103 (2017) - [i1]Peter Bloem, Steven de Rooij:
An Expectation-Maximization Algorithm for the Fractal Inverse Problem. CoRR abs/1706.03149 (2017) - 2016
- [c6]Steven de Rooij, Wouter Beek, Peter Bloem, Frank van Harmelen, Stefan Schlobach:
Are Names Meaningful? Quantifying Social Meaning on the Semantic Web. ISWC (1) 2016: 184-199 - 2015
- [c5]Peter Bloem, Steven de Rooij, Pieter Adriaans:
Two Problems for Sophistication. ALT 2015: 379-394 - 2014
- [c4]Peter Bloem, Francisco Mota, Steven de Rooij, Luis Antunes, Pieter Adriaans:
A Safe Approximation for Kolmogorov Complexity. ALT 2014: 336-350 - [c3]Peter Bloem, Adianto Wibisono, Gerben de Vries:
Simplifying RDF Data for Graph-Based Machine Learning. KNOW@LOD 2014 - [c2]Adianto Wibisono, Peter Bloem, Gerben Klaas Dirk de Vries, Paul Groth, Adam Belloum, Marian Bubak:
Generating Scientific Documentation for Computational Experiments Using Provenance. IPAW 2014: 168-179 - [c1]Peter Bloem, Gerben de Vries:
Machine Learning on Linked Data, a Position Paper. LD4KD 2014
Coauthor Index
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last updated on 2024-11-08 20:31 CET by the dblp team
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