Maximilian Nickel

According to our database1, Maximilian Nickel authored at least 37 papers between 2011 and 2020.

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Bibliography

2020
Neural Spatio-Temporal Point Processes.
CoRR, 2020

Learning Neural Event Functions for Ordinary Differential Equations.
CoRR, 2020

CURI: A Benchmark for Productive Concept Learning Under Uncertainty.
CoRR, 2020

Riemannian Continuous Normalizing Flows.
CoRR, 2020

Learning Multivariate Hawkes Processes at Scale.
CoRR, 2020

2019
Hyperbolic Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Task-Driven Modular Networks for Zero-Shot Compositional Learning.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Revisiting the Evaluation of Theory of Mind through Question Answering.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Relational Models.
Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Learning Visually Grounded Sentence Representations.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry.
Proceedings of the 35th International Conference on Machine Learning, 2018

Separating Self-Expression and Visual Content in Hashtag Supervision.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017
Complex and Holographic Embeddings of Knowledge Graphs: A Comparison.
CoRR, 2017

Poincaré Embeddings for Learning Hierarchical Representations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Fast Linear Model for Knowledge Graph Embeddings.
Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

2016
A Review of Relational Machine Learning for Knowledge Graphs.
Proc. IEEE, 2016

Relational Models.
CoRR, 2016

Holographic Embeddings of Knowledge Graphs.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
A Review of Relational Machine Learning for Knowledge Graphs: From Multi-Relational Link Prediction to Automated Knowledge Graph Construction.
CoRR, 2015

2014
Querying the Web with Statistical Machine Learning.
Proceedings of the Towards the Internet of Services: The THESEUS Research Program, 2014

Relational Models.
Encyclopedia of Social Network Analysis and Mining, 2014

A scalable approach for statistical learning in semantic graphs.
Semantic Web, 2014

Querying Factorized Probabilistic Triple Databases.
Proceedings of the Semantic Web - ISWC 2014, 2014

Probabilistic Latent-Factor Database Models.
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

Reducing the Rank in Relational Factorization Models by Including Observable Patterns.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Large-scale factorization of type-constrained multi-relational data.
Proceedings of the International Conference on Data Science and Advanced Analytics, 2014

2013
Tensor factorization for relational learning.
PhD thesis, 2013

Logistic Tensor Factorization for Multi-Relational Data.
CoRR, 2013

Tensor Factorization for Multi-relational Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

An Analysis of Tensor Models for Learning on Structured Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

2012
Factorizing YAGO: scalable machine learning for linked data.
Proceedings of the 21st World Wide Web Conference 2012, 2012

Link Prediction in Multi-relational Graphs using Additive Models.
Proceedings of the International Workshop on Semantic Technologies meet Recommender Systems & Big Data, 2012

Scalable Relation Prediction Exploiting Both Intrarelational Correlation and Contextual Information.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Combining Information Extraction, Deductive Reasoning and Machine Learning for Relation Prediction.
Proceedings of the Semantic Web: Research and Applications, 2012

2011
A Three-Way Model for Collective Learning on Multi-Relational Data.
Proceedings of the 28th International Conference on Machine Learning, 2011


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