Learning Aggregation Functions

Uninorm aggregation operators

Ronald R Yager and Alexander Rybalov · 1996

Earlier work this paper cites.

Bayesian sets

Zoubin Ghahramani and Katherine A Heller · 2006

Earlier work this paper cites.

3d is here: Point cloud library (pcl)

Radu Bogdan Rusu and Steve Cousins · 2011

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Distributed representations of words and phrases and their compositionality

Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013

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Convolutional neural networks for sentence classification

Yoon Kim · 2014

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Neural machine translation by jointly learning to align and translate

Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015

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3d shapenets: A deep representation for volumetric shapes

Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015

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Learning to aggregate using uninorms

Vitalik Melnikov and Eyke Hüllermeier · 2016

Cited alongside, same era.

Inductive representation learning on large graphs

William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017

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Semi-supervised classification with graph convolutional networks

Thomas N. Kipf and Max Welling · 2017

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A simple neural network module for relational reasoning

Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Timothy Lillicrap · 2017

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Attention is all you need

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017

Cited alongside, same era.

Deep sets

Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Russ R Salakhutdinov, and Alexander J Smola · 2017

Cited alongside, same era.

Graph attention networks

Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018

Later among the works it cites.

Set transformer: A framework for attention-based permutation-invariant neural networks

Juho Lee, Yoonho Lee, Jungtaek Kim, Adam R. Kosiorek, Seungjin Choi, and Yee Whye Teh · 2019

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On the limitations of representing functions on sets

Original

Edward Wagstaff, Fabian B Fuchs, Martin Engelcke, Ingmar Posner, and Michael Osborne · 2019

Later among the works it cites.

How powerful are graph neural networks?

Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2019

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Principal neighbourhood aggregation for graph nets

Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, and Petar Velickovic · 2020

Closest in time.

Learning and interpreting multi-multi-instance learning networks