Fetching the paper…
Reading the bibliography…
We propose Embedding Propagation (EP), an unsupervised learning framework for graph-structured data.
Multidimensional scaling
J. B. Kruskal and M. Wish · 1978
Earlier work this paper cites.
Generalization of back-propagation to recurrent neural networks
F. J. Pineda · 1987
Earlier work this paper cites.
Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
P. J. Rousseeuw · 1987
Earlier work this paper cites.
Artificial neural networks
L. B. Almeida · 1990
Earlier work this paper cites.
Signature verification using a "siamese" time delay neural network
J. Bromley, I. Guyon, Y. Lecun, E. Säckinger, and R. Shah · 1994
Earlier work this paper cites.
The pagerank citation ranking: bringing order to the web
L. Page, S. Brin, R. Motwani, and T. Winograd · 1999
Earlier work this paper cites.
Nonlinear dimensionality reduction by locally linear embedding
S. T. Roweis and L. K. Saul · 2000
Earlier work this paper cites.
A global geometric framework for nonlinear dimensionality reduction
J. B. Tenenbaum, V. De Silva, and J. C. Langford · 2000
Earlier work this paper cites.
Laplacian eigenmaps and spectral techniques for embedding and clustering
M. Belkin and P. Niyogi · 2001
Earlier work this paper cites.
Learning from labeled and unlabeled data with label propagation
X. Zhu and Z. Ghahramani · 2002
Earlier work this paper cites.
A simple relational classifier
S. A. Macskassy and F. Provost · 2003
Earlier work this paper cites.
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
L. Getoor and B. Taskar · 2007
Earlier work this paper cites.
The link-prediction problem for social networks
D. Liben-Nowell and J. Kleinberg · 2007
Earlier work this paper cites.
A tutorial on spectral clustering
U. Luxburg · 2007
Earlier work this paper cites.
The biogrid interaction database: 2008 update
B.-J. Breitkreutz, C. Stark, T. Reguly, L. Boucher, A. Breitkreutz, M. Livstone, R. Oughtred, D. H. Lackner, J. Bähler, V. Wood, et al · 2008
Earlier work this paper cites.
Liblinear: A library for large linear classification
R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin · 2008
Earlier work this paper cites.
Visualizing data using t-sne
L. v. d. Maaten and G. Hinton · 2008
Cited alongside, same era.
Collective classification in network data
P. Sen, G. M. Namata, M. Bilgic, L. Getoor, B. Gallagher, and T. Eliassi-Rad · 2008
Cited alongside, same era.
Anomaly detection: A survey
V. Chandola, A. Banerjee, and V. Kumar · 2009
Cited alongside, same era.
Large text compression benchmark
M. Mahoney · 2009
Cited alongside, same era.
The graph neural network model
F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini · 2009
Cited alongside, same era.
Relational learning via latent social dimensions
L. Tang and H. Liu · 2009
Cited alongside, same era.
Social computing data repository at asu
R. Zafarani and H. Liu · 2009
Devise: A deep visual-semantic embedding model
A. Frome, G. S. Corrado, J. Shlens, S. Bengio, J. Dean, T. Mikolov, et al · 2013
Later among the works it cites.
Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean · 2013
Later among the works it cites.
Graphx: A resilient distributed graph system on spark
R. S. Xin, J. E. Gonzalez, M. J. Franklin, and I. Stoica · 2013
Later among the works it cites.
Power iterated color refinement
K. Kersting, M. Mladenov, R. Garnett, and M. Grohe · 2014
Later among the works it cites.
Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
Later among the works it cites.
Deepwalk: Online learning of social representations
B. Perozzi, R. Al-Rfou, and S. Skiena · 2014
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Theano: A cpu and gpu math compiler in python
J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian, D. Warde-Farley, and Y. Bengio · 2010
Cited alongside, same era.
Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
Cited alongside, same era.
Graphlab: A new parallel framework for machine learning
Y. Low, J. Gonzalez, A. Kyrola, D. Bickson, C. Guestrin, and J. M. Hellerstein · 2010
Cited alongside, same era.
Pregel: A system for large-scale graph processing
G. Malewicz, M. H. Austern, A. J. Bik, J. C. Dehnert, I. Horn, N. Leiser, and G. Czajkowski · 2010
Cited alongside, same era.
Link prediction in complex networks: A survey
L. Lü and T. Zhou · 2011
Cited alongside, same era.
Later among the works it cites.
Graph based anomaly detection and description: a survey
L. Akoglu, H. Tong, and D. Koutra · 2015
Later among the works it cites.
Gated graph sequence neural networks
Y. Li, D. Tarlow, M. Brockschmidt, and R. Zemel · 2015
Later among the works it cites.
Line: Large-scale information network embedding
J. Tang, M. Qu, M. Wang, M. Zhang, J. Yan, and Q. Mei · 2015
Later among the works it cites.
Node2vec: Scalable feature learning for networks
A. Grover and J. Leskovec · 2016
Later among the works it cites.
Semi-supervised classification with graph convolutional networks
T. N. Kipf and M. Welling · 2016
Later among the works it cites.
A review of relational machine learning for knowledge graphs
M. Nickel, K. Murphy, V. Tresp, and E. Gabrilovich · 2016
Later among the works it cites.
Statistical relational artificial intelligence: Logic, probability, and computation
L. D. Raedt, K. Kersting, S. Natarajan, and D. Poole · 2016
Later among the works it cites.
Revisiting semi-supervised learning with graph embeddings
Z. Yang, W. W. Cohen, and R. Salakhutdinov · 2016
Later among the works it cites.
Neural message passing for quantum chemistry
J. Gilmer, S. S. Schoenholz, P. F. Riley, O. Vinyals, and G. E. Dahl · 2017
Closest in time.