Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs

5 November 2018

R. Murphy

Balasubramaniam Srinivasan

Vinayak A. Rao

Yun Liang

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Papers citing "Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs"

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Neural Discovery of Permutation Subgroups Pavan Karjol Rohan Kashyap A. Prathosh 28 3 0 11 Sep 2023
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Learnable Commutative Monoids for Graph Neural Networks Euan Ong Petar Velickovic 18 12 0 16 Dec 2022
SELTO: Sample-Efficient Learned Topology Optimization Sören Dittmer David Erzmann Henrik Harms Peter Maass 32 2 0 12 Sep 2022
The Neural Process Family: Survey, Applications and Perspectives Saurav Jha Dong Gong Xuesong Wang Richard Turner L. Yao BDL 73 24 0 01 Sep 2022
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling Tung Nguyen Aditya Grover BDL UQCV 19 99 0 09 Jul 2022
Universally Expressive Communication in Multi-Agent Reinforcement Learning Matthew Morris Thomas D. Barrett Arnu Pretorius 24 4 0 14 Jun 2022
Exponential Separations in Symmetric Neural Networks Aaron Zweig Joan Bruna 29 7 0 02 Jun 2022
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs Yangze Zhou Gitta Kutyniok Bruno Ribeiro OODD AI4CE 78 37 0 30 May 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
Equilibrium Aggregation: Encoding Sets via Optimization Sergey Bartunov F. Fuchs Timothy Lillicrap 24 7 0 25 Feb 2022
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Neural Operator: Learning Maps Between Function Spaces Nikola B. Kovachki Zong-Yi Li Burigede Liu Kamyar Azizzadenesheli K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 40 440 0 19 Aug 2021
Universal Approximation of Functions on Sets E. Wagstaff F. Fuchs Martin Engelcke Michael A. Osborne Ingmar Posner PINN 35 54 0 05 Jul 2021
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks Eli Chien Chao Pan Jianhao Peng O. Milenkovic GNN 41 128 0 24 Jun 2021
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs Mikhail Galkin E. Denis Jiapeng Wu William L. Hamilton OCL 25 86 0 23 Jun 2021
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 32 347 0 18 Feb 2021
Regularizing Towards Permutation Invariance in Recurrent Models Edo Cohen-Karlik Avichai Ben David Amir Globerson OOD 16 15 0 25 Oct 2020
End-to-End Differentiable Molecular Mechanics Force Field Construction Yuanqing Wang Josh Fass Benjamin Kaminow John E. Herr Dominic Rufa Ivy Zhang Iván Pulido Mike Henry J. Chodera 19 23 0 02 Oct 2020
Expressive Power of Invariant and Equivariant Graph Neural Networks Waïss Azizian Marc Lelarge 28 111 0 28 Jun 2020
Subgraph Neural Networks Emily Alsentzer S. G. Finlayson Michelle M. Li Marinka Zitnik GNN 18 134 0 18 Jun 2020
Multipole Graph Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 24 375 0 16 Jun 2020
On Learning Sets of Symmetric Elements Haggai Maron Or Litany Gal Chechik Ethan Fetaya 30 132 0 20 Feb 2020
Generalization and Representational Limits of Graph Neural Networks Vikas K. Garg Stefanie Jegelka Tommi Jaakkola GNN 26 304 0 14 Feb 2020
Random Features Strengthen Graph Neural Networks Ryoma Sato M. Yamada H. Kashima GNN AAML 13 232 0 08 Feb 2020
Learn to Predict Sets Using Feed-Forward Neural Networks H. Rezatofighi Tianyu Zhu Roman Kaskman F. Motlagh Javen Qinfeng Shi Anton Milan Daniel Cremers Laura Leal-Taixé Ian Reid SSL 61 15 0 30 Jan 2020
On the Equivalence between Positional Node Embeddings and Structural Graph Representations Balasubramaniam Srinivasan Bruno Ribeiro 17 27 0 01 Oct 2019
Relational Pooling for Graph Representations R. Murphy Balasubramaniam Srinivasan Vinayak A. Rao Bruno Ribeiro GNN 33 256 0 06 Mar 2019
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation Samuel Wiqvist Pierre-Alexandre Mattei Umberto Picchini J. Frellsen BDL 30 32 0 29 Jan 2019
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,944 0 09 Jun 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016