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Neural Spatio-Temporal Point Processes


Nov 09, 2020
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel


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Learning Neural Event Functions for Ordinary Differential Equations


Nov 08, 2020
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel


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CURI: A Benchmark for Productive Concept Learning Under Uncertainty


Oct 06, 2020
Ramakrishna Vedantam, Arthur Szlam, Maximilian Nickel, Ari Morcos, Brenden Lake


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Riemannian Continuous Normalizing Flows


Jun 18, 2020
Emile Mathieu, Maximilian Nickel


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Learning Multivariate Hawkes Processes at Scale


Feb 28, 2020
Maximilian Nickel, Matthew Le


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Hyperbolic Graph Neural Networks


Oct 28, 2019
Qi Liu, Maximilian Nickel, Douwe Kiela

* Published at NeurIPS 2019 

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Task-Driven Modular Networks for Zero-Shot Compositional Learning


May 15, 2019
Senthil Purushwalkam, Maximilian Nickel, Abhinav Gupta, Marc'Aurelio Ranzato

* http://www.cs.cmu.edu/~spurushw/projects/compositional.html 

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Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings


Feb 03, 2019
Matt Le, Stephen Roller, Laetitia Papaxanthos, Douwe Kiela, Maximilian Nickel


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Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry


Jul 08, 2018
Maximilian Nickel, Douwe Kiela

* Accepted at ICML'18 

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Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora


Jun 08, 2018
Stephen Roller, Douwe Kiela, Maximilian Nickel

* Accepted as a short paper to ACL 2018 

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Learning Visually Grounded Sentence Representations


Jun 04, 2018
Douwe Kiela, Alexis Conneau, Allan Jabri, Maximilian Nickel

* Published at NAACL-18 

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Separating Self-Expression and Visual Content in Hashtag Supervision


Nov 27, 2017
Andreas Veit, Maximilian Nickel, Serge Belongie, Laurens van der Maaten


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Fast Linear Model for Knowledge Graph Embeddings


Oct 30, 2017
Armand Joulin, Edouard Grave, Piotr Bojanowski, Maximilian Nickel, Tomas Mikolov

* Submitted AKBC 2017 

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Complex and Holographic Embeddings of Knowledge Graphs: A Comparison


Jul 23, 2017
Théo Trouillon, Maximilian Nickel


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Poincaré Embeddings for Learning Hierarchical Representations


May 26, 2017
Maximilian Nickel, Douwe Kiela


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Relational Models


Sep 11, 2016
Volker Tresp, Maximilian Nickel


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Holographic Embeddings of Knowledge Graphs


Dec 07, 2015
Maximilian Nickel, Lorenzo Rosasco, Tomaso Poggio

* To appear in AAAI-16 

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A Review of Relational Machine Learning for Knowledge Graphs


Sep 28, 2015
Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich

* To appear in Proceedings of the IEEE 

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Logistic Tensor Factorization for Multi-Relational Data


Jun 10, 2013
Maximilian Nickel, Volker Tresp

* Accepted at ICML 2013 Workshop "Structured Learning: Inferring Graphs from Structured and Unstructured Inputs" (SLG 2013) 

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