Maximilian Nickel
Maximilian Nickel
Research Scientist at Facebook AI Research
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A Three-Way Model for Collective Learning on Multi-Relational Data
M Nickel, V Tresp, HP Kriegel
Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011
12582011
A Review of Relational Machine Learning for Knowledge Graphs
M Nickel, K Murphy, V Tresp, E Gabrilovich
arXiv preprint arXiv:1503.00759, 2015
10382015
Holographic embeddings of knowledge graphs
M Nickel, L Rosasco, T Poggio
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
6502016
Poincaré Embeddings for Learning Hierarchical Representations
M Nickel, D Kiela
arXiv preprint arXiv:1705.08039, 2017
5192017
Factorizing YAGO: Scalable Machine Learning for Linked Data
M Nickel, V Tresp, HP Kriegel
Proceedings of the 21st International Conference on World Wide Web, 271-280, 2012
3982012
Learning continuous hierarchies in the lorentz model of hyperbolic geometry
M Nickel, D Kiela
International Conference on Machine Learning, 3779-3788, 2018
1472018
Reducing the Rank in Relational Factorization Models by Including Observable Patterns.
M Nickel, X Jiang, V Tresp
NIPS, 1179-1187, 2014
852014
Tensor factorization for multi-relational learning
M Nickel, V Tresp
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2013
842013
Hearst patterns revisited: Automatic hypernym detection from large text corpora
S Roller, D Kiela, M Nickel
arXiv preprint arXiv:1806.03191, 2018
652018
Logistic tensor factorization for multi-relational data
M Nickel, V Tresp
arXiv preprint arXiv:1306.2084, 2013
502013
Learning visually grounded sentence representations
D Kiela, A Conneau, A Jabri, M Nickel
arXiv preprint arXiv:1707.06320, 2017
482017
Hyperbolic graph neural networks
Q Liu, M Nickel, D Kiela
arXiv preprint arXiv:1910.12892, 2019
462019
Inferring concept hierarchies from text corpora via hyperbolic embeddings
M Le, S Roller, L Papaxanthos, D Kiela, M Nickel
arXiv preprint arXiv:1902.00913, 2019
372019
Non-negative tensor factorization with rescal
D Krompaß, M Nickel, X Jiang, V Tresp
Tensor Methods for Machine Learning, ECML workshop, 1-10, 2013
352013
Querying factorized probabilistic triple databases
D Krompaß, M Nickel, V Tresp
International Semantic Web Conference, 114-129, 2014
312014
A scalable approach for statistical learning in semantic graphs
Y Huang, V Tresp, M Nickel, A Rettinger, HP Kriegel
Semantic Web 5 (1), 5-22, 2014
312014
Link Prediction in Multi-relational Graphs using Additive Models.
X Jiang, V Tresp, Y Huang, M Nickel
SeRSy 919, 1-12, 2012
312012
Complex and holographic embeddings of knowledge graphs: a comparison
T Trouillon, M Nickel
arXiv preprint arXiv:1707.01475, 2017
282017
Task-driven modular networks for zero-shot compositional learning
S Purushwalkam, M Nickel, A Gupta, MA Ranzato
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
262019
Fast linear model for knowledge graph embeddings
A Joulin, E Grave, P Bojanowski, M Nickel, T Mikolov
arXiv preprint arXiv:1710.10881, 2017
252017
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Artikkelit 1–20