Fetching the paper…
Reading the bibliography…
Interest has been rising lately towards methods representing data in non-Euclidean spaces, e.g.
Deepsphere: towards an equivariant graph-based spherical cnn
Defferrard, M., Perraudin, N., Kacprzak, T., and Sgier, R · 1904
Earlier work this paper cites.
A comprehensive introduction to differential geometry. volume four
Spivak, M · 1979
Earlier work this paper cites.
Hyperbolic groups
Gromov, M · 1987
Earlier work this paper cites.
Geometry of Cuts and Metrics
Deza, M. and Laurent, M · 1996
Earlier work this paper cites.
The hyperbolic pythagorean theorem in the Poincaré disc model of hyperbolic geometry
Ungar, A. A · 1999
Earlier work this paper cites.
Automating the construction of internet portals with machine learning
McCallum, A., Nigam, K., Rennie, J., and Seymore, K · 2000
Earlier work this paper cites.
Nonlinear dimensionality reduction by locally linear embedding
Roweis, S. T. and Saul, L. K · 2000
Earlier work this paper cites.
A global geometric framework for nonlinear dimensionality reduction
Tenenbaum, J. B., De Silva, V., and Langford, J. C · 2000
Earlier work this paper cites.
Analytic hyperbolic geometry: Mathematical foundations and applications
Ungar, A. A · 2005
Earlier work this paper cites.
Methods of information geometry , volume 191
Amari, S.-i. and Nagaoka, H · 2007
Earlier work this paper cites.
Collective Classification in Network Data
Sen, P., Namata, G., Bilgic, M., Getoor, L., Gallagher, B., and Eliassi-Rad, T · 2008
Earlier work this paper cites.
A gyrovector space approach to hyperbolic geometry
Ungar, A. A · 2008
Earlier work this paper cites.
Hyperbolic geometry of complex networks
Krioukov, D., Papadopoulos, F., Kitsak, M., Vahdat, A., and Boguná, M · 2010
Earlier work this paper cites.
Barycentric Calculus in Euclidean and Hyperbolic Geometry
Ungar, A · 2010
Earlier work this paper cites.
Wavelets on graphs via spectral graph theory
Hammond, D. K., Vandergheynst, P., and Gribonval, R · 2011
Earlier work this paper cites.
Low distortion delaunay embedding of trees in hyperbolic plane
Sarkar, R · 2011
Earlier work this paper cites.
Query-driven Active Surveying for Collective Classification
Namata, G., London, B., Getoor, L., and Huang, B · 2012
Earlier work this paper cites.
Deep learning via semi-supervised embedding
Weston, J., Ratle, F., Mobahi, H., and Collobert, R · 2012
Earlier work this paper cites.
Speech recognition with deep recurrent neural networks
Graves, A., Mohamed, A.-r., and Hinton, G · 2013
Earlier work this paper cites.
Lecture notes on metric embeddings
Matousek, J · 2013
Earlier work this paper cites.
Spectral networks and locally connected networks on graphs
Bruna, J., Zaremba, W., Szlam, A., and Lecun, Y · 2014
Cited alongside, same era.
Analytic Hyperbolic Geometry in N Dimensions: An Introduction
Ungar, A. A · 2014
Cited alongside, same era.
Spherical and hyperbolic embeddings of data
Wilson, R. C., Hancock, E. R., Pekalska, E., and Duin, R. P · 2014
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Bahdanau, D., Cho, K., and Bengio, Y · 2015
Cited alongside, same era.
Deep convolutional networks on graph-structured data
Henaff, M., Bruna, J., and LeCun, Y · 2015
Cited alongside, same era.
ADAM: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2015
N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification
Abu-El-Haija, S., Kapoor, A., Perozzi, B., and Lee, J · 2018
Later among the works it cites.
Fastgcn: fast learning with graph convolutional networks via importance sampling
Chen, J., Ma, T., and Xiao, C · 2018
Later among the works it cites.
Hyperspherical Variational Auto-Encoders
Davidson, T. R., Falorsi, L., De Cao, N., Kipf, T., and Tomczak, J. M · 2018
Later among the works it cites.
Learning graph embeddings on constant-curvature manifolds for change detection in graph streams
Grattarola, D., Zambon, D., Alippi, C., and Livi, L · 2018
Later among the works it cites.
Hyperbolic attention networks
Gulcehre, C., Denil, M., Malinowski, M., Razavi, A., Pascanu, R., Hermann, K. M., Battaglia, P., Bapst, V., Raposo, D., Santoro, A., et al · 2018
Later among the works it cites.
Learning continuous hierarchies in the lorentz model of hyperbolic geometry
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Convolutional neural networks on graphs with fast localized spectral filtering
Defferrard, M., Bresson, X., and Vandergheynst, P · 2016
Cited alongside, same era.
Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
Cited alongside, same era.
Novel tools to determine hyperbolic triangle centers
Ungar, A. A · 2016
Cited alongside, same era.
Link prediction based on graph neural networks
Zhang, M. and Chen, Y · 2016
Cited alongside, same era.
Geometric deep learning: going beyond euclidean data
Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., and Vandergheynst, P · 2017
Cited alongside, same era.
Neural Message Passing for Quantum Chemistry
Gilmer, J., Schoenholz, S. S., Riley, P. F., Vinyals, O., and Dahl, G. E · 2017
Cited alongside, same era.
Nickel, M. and Kiela, D · 2018
Later among the works it cites.
Representation tradeoffs for hyperbolic embeddings
Sala, F., De Sa, C., Gu, A., and Re, C · 2018
Later among the works it cites.
Graph attention networks
Veličković, P., Cucurull, G., Casanova, A., Romero, A., Liò, P., and Bengio, Y · 2018
Later among the works it cites.
Spherical latent spaces for stable variational autoencoders
Xu, J. and Durrett, G · 2018
Later among the works it cites.
How powerful are graph neural networks?
Xu, K., Hu, W., Leskovec, J., and Jegelka, S · 2018
Later among the works it cites.
Hyperbolic graph convolutional neural networks
Chami, I., Ying, R., Ré, C., and Leskovec, J · 2019
Closest in time.
Large-margin classification in hyperbolic space
Cho, H., DeMeo, B., Peng, J., and Berger, B · 2019
Closest in time.
Learning mixed-curvature representations in product spaces
Gu, A., Sala, F., Gunel, B., and Ré, C · 2019
Closest in time.
Predict then propagate: graph neural networks meet personalized pagerank
Klicpera, J., Bojchevski, A., and Günnemann, S · 2019
Closest in time.
Hyperbolic graph neural networks
Liu, Q., Nickel, M., and Kiela, D · 2019
Closest in time.
Continuous hierarchical representations with Poincaré variational auto-encoders
Mathieu, E., Lan, C. L., Maddison, C. J., Tomioka, R., and Teh, Y. W · 2019
Closest in time.
Poincaré Wasserstein autoencoder
Ovinnikov, I · 2019
Closest in time.
Poincaré glove: Hyperbolic word embeddings
Tifrea, A., Bécigneul, G., and Ganea, O.-E · 2019
Closest in time.
A comprehensive survey on graph neural networks
Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., and Yu, P. S · 2019
Closest in time.