Fetching the paper…
Reading the bibliography…
We study the problem of modeling a binary operation that satisfies some algebraic requirements.
“On some semi-groups”
Reikichi Yoshida · 1963
Earlier work this paper cites.
“Approximation by superpositions of a sigmoidal function”
G. Cybenko · 1989
Earlier work this paper cites.
“Backpropagation Applied to Handwritten Zip Code Recognition”
Y. LeCun et al · 1989
Earlier work this paper cites.
“Multilayer Feedforward Networks with a Non-Polynomial Activation Function Can Approximate Any Function”
M. Leshno, Vladimir. Lin, A. Pinkus and S. Schocken · 1993
Earlier work this paper cites.
“Monotonic Networks”
J. Sill · 1997
Earlier work this paper cites.
“Lie groups. An approach through invariants and representations”
Claudio Procesi · 2007
Earlier work this paper cites.
“Software Framework for Topic Modelling with Large Corpora”
Radim Řehůřek and Petr Sojka · 2010
Earlier work this paper cites.
“DENSITY ESTIMATION BY DUAL ASCENT OF THE LOG-LIKELIHOOD”
E. Tabak and E. Vanden-Eijnden · 2010
Earlier work this paper cites.
“WSABIE: Scaling Up to Large Vocabulary Image Annotation”
J. Weston, S. Bengio and Nicolas Usunier · 2011
Earlier work this paper cites.
“Efficient Estimation of Word Representations in Vector Space”
Tomas Mikolov, Kai Chen, G.. Corrado and J. Dean · 2013
Earlier work this paper cites.
“Distributed Representations of Words and Phrases and their Compositionality”
Tomas Mikolov et al · 2013
Earlier work this paper cites.
“NICE: Non-linear Independent Components Estimation”
Laurent Dinh, David Krueger and Yoshua Bengio · 2015
Earlier work this paper cites.
“Adam: A Method for Stochastic Optimization”
Diederik. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
“Interaction Networks for Learning about Objects, Relations and Physics”
Peter Battaglia et al · 2016
Earlier work this paper cites.
“Group Equivariant Convolutional Networks”
Taco Cohen and Max Welling · 2016
Earlier work this paper cites.
“Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn’t”
Anna Rogers, Aleksandr Drozd and S. Matsuoka · 2016
Earlier work this paper cites.
“Density estimation using Real NVP”
Laurent Dinh, Jascha Sohl-Dickstein and S. Bengio · 2017
Earlier work this paper cites.
“Neural Message Passing for Quantum Chemistry”
J. Gilmer et al · 2017
Earlier work this paper cites.
“Learning Combinatorial Optimization Algorithms over Graphs”
Elias Khalil et al · 2017
Cited alongside, same era.
“Improved Variational Inference with Inverse Autoregressive Flow”
Diederik. Kingma, Tim Salimans and M. Welling · 2017
Cited alongside, same era.
“Semi-Supervised Classification with Graph Convolutional Networks”
Thomas Kipf and M. Welling · 2017
Cited alongside, same era.
“The Expressive Power of Neural Networks: A View from the Width”
Zhou Lu et al · 2017
Cited alongside, same era.
“The Expressive Power of Neural Networks: A View from the Width”
Zhou Lu et al · 2017
Cited alongside, same era.
“PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation”
C.. Qi, H. Su, Kaichun Mo and L. Guibas · 2017
Cited alongside, same era.
“Neural Spline Flows”
Conor Durkan, A. Bekasov, Iain Murray and George Papamakarios · 2019
Later among the works it cites.
“Sum-of-Squares Polynomial Flow”
Priyank Jaini, Kira. Selby and Yaoliang Yu · 2019
Later among the works it cites.
“Universal Invariant and Equivariant Graph Neural Networks”
N. Keriven and G. Peyré · 2019
Later among the works it cites.
“A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks”
T. Maehara and NT Hoang · 2019
Later among the works it cites.
“On the Universality of Invariant Networks”
Haggai Maron, Ethan Fetaya, Nimrod Segol and Y. Lipman · 2019
Later among the works it cites.
“On the Universality of Invariant Networks”
Haggai Maron, Ethan Fetaya, Nimrod Segol and Yaron Lipman · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
“Attention is All you Need”
Ashish Vaswani et al · 2017
Cited alongside, same era.
“Harmonic Networks: Deep Translation and Rotation Equivariance”
Daniel. Worrall, Stephan. Garbin, Daniyar Turmukhambetov and Gabriel. Brostow · 2017
Cited alongside, same era.
“Deep Sets”
M. Zaheer et al · 2017
Cited alongside, same era.
“Relational inductive biases, deep learning, and graph networks”
P. Battaglia et al · 2018
Cited alongside, same era.
“Neural Ordinary Differential Equations”
Tian Chen, Yulia Rubanova, J. Bettencourt and D. Duvenaud · 2018
Cited alongside, same era.
“Neural Autoregressive Flows”
C. Huang, David Krueger, Alexandre Lacoste and Aaron. Courville · 2018
Cited alongside, same era.
“Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks”
C. Morris et al · 2019
Later among the works it cites.
“Normalizing Flows for Probabilistic Modeling and Inference”
George Papamakarios et al · 2019
Later among the works it cites.
“PyTorch: An Imperative Style, High-Performance Deep Learning Library”
Adam Paszke et al · 2019
Later among the works it cites.
“Approximation Ratios of Graph Neural Networks for Combinatorial Problems”
R. Sato, M. Yamada and H. Kashima · 2019
Later among the works it cites.
“How Powerful are Graph Neural Networks?”
Keyulu Xu, Weihua Hu, J. Leskovec and S. Jegelka · 2019
Later among the works it cites.
“Normalizing Flows: An Introduction and Review of Current Methods.”
I. Kobyzev, S. Prince and M. Brubaker · 2020
Later among the works it cites.
“On Learning Sets of Symmetric Elements”
Haggai Maron, Or Litany, Gal Chechik and Ethan Fetaya · 2020
Later among the works it cites.
“Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators”
Takeshi Teshima et al · 2020
Later among the works it cites.
“Neural Execution of Graph Algorithms”
Petar Veličković et al · 2020
Later among the works it cites.
“On Size Generalization in Graph Neural Networks”
Gilad Yehudai et al · 2020
Later among the works it cites.
“How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks”
Keyulu Xu et al · 2021
Closest in time.