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Hyperbolic spaces have recently gained momentum in the context of machine learning due to their high capacity and tree-likeliness properties.
A comprehensive introduction to differential geometry
Michael Spivak · 1979
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Hyperbolic groups
Mikhael Gromov · 1987
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A focus+ context technique based on hyperbolic geometry for visualizing large hierarchies
John Lamping, Ramana Rao, and Peter Pirolli · 1995
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Hyperbolic geometry
James W Cannon, William J Floyd, Richard Kenyon, Walter R Parry, et al · 1997
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The hyperbolic derivative in the poincaré ball model of hyperbolic geometry
Graciela S Birman and Abraham A Ungar · 2001
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Hyperbolic trigonometry and its application in the poincaré ball model of hyperbolic geometry
Abraham A Ungar · 2001
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Hyperplane margin classifiers on the multinomial manifold
Guy Lebanon and John Lafferty · 2004
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A geometric interpretation of ungar’s addition and of gyration in the hyperbolic plane
J Vermeer · 2005
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Analytic hyperbolic geometry and Albert Einstein’s special theory of relativity
Ungar Abraham Albert · 2008
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A gyrovector space approach to hyperbolic geometry
Abraham Albert Ungar · 2008
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The Ricci flow in Riemannian geometry
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Hyperbolic geometry of complex networks
Dmitri Krioukov, Fragkiskos Papadopoulos, Maksim Kitsak, Amin Vahdat, and Marián Boguná · 2010
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A three-way model for collective learning on multi-relational data
Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel · 2011
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Stochastic gradient descent on riemannian manifolds
S. Bonnabel · 2013
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Convolutional neural networks for sentence classification
Yoon Kim · 2014
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Reasoning about entailment with neural attention
Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomáš Kočiskỳ, and Phil Blunsom · 2015
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Tensorflow: A system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al · 2016
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Order-embeddings of images and language
Ivan Vendrov, Ryan Kiros, Sanja Fidler, and Raquel Urtasun · 2016
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Geometric deep learning: going beyond euclidean data
Michael M Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
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On the tree-likeness of hyperbolic spaces
Matthias Hamann · 2017
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Poincaré embeddings for learning hierarchical representations
Maximillian Nickel and Douwe Kiela · 2017
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Analytic hyperbolic geometry in n dimensions: An introduction
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Neural machine translation by jointly learning to align and translate
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Representation tradeoffs for hyperbolic embeddings
Christopher De Sa, Albert Gu, Christopher Ré, and Frederic Sala · 2018
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Hyperbolic entailment cones for learning hierarchical embeddings
Octavian-Eugen Ganea, Gary Bécigneul, and Thomas Hofmann · 2018
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Can recurrent neural networks warp time?
Corentin Tallec and Yann Ollivier · 2018
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