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Deep Sets
v1v2v3 (latest)

Deep Sets

10 March 2017
Manzil Zaheer
Satwik Kottur
Siamak Ravanbakhsh
Barnabás Póczós
Ruslan Salakhutdinov
Alex Smola
ArXiv (abs)PDFHTML

Papers citing "Deep Sets"

50 / 1,556 papers shown
Ego-based Entropy Measures for Structural Representations
Ego-based Entropy Measures for Structural Representations
George Dasoulas
Giannis Nikolentzos
Kevin Scaman
Aladin Virmaux
Michalis Vazirgiannis
119
4
0
01 Mar 2020
Estimating the Effects of Continuous-valued Interventions using
  Generative Adversarial Networks
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial NetworksNeural Information Processing Systems (NeurIPS), 2020
Ioana Bica
James Jordon
M. Schaar
CML
287
116
0
27 Feb 2020
GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion
  Planning with End-to-End Learning
GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning with End-to-End LearningIEEE Robotics and Automation Letters (RA-L), 2020
Benjamin Rivière
Wolfgang Hoenig
Yisong Yue
Soon-Jo Chung
169
101
0
26 Feb 2020
Predicting Neural Network Accuracy from Weights
Predicting Neural Network Accuracy from Weights
Thomas Unterthiner
Daniel Keysers
Sylvain Gelly
Olivier Bousquet
Ilya O. Tolstikhin
438
120
0
26 Feb 2020
Adversarial Monte Carlo Meta-Learning of Optimal Prediction Procedures
Adversarial Monte Carlo Meta-Learning of Optimal Prediction ProceduresJournal of machine learning research (JMLR), 2020
Alexander Luedtke
Incheoul Chung
Oleg Sofrygin
176
4
0
26 Feb 2020
Learning the mapping $\mathbf{x}\mapsto \sum_{i=1}^d x_i^2$: the cost of
  finding the needle in a haystack
Learning the mapping x↦∑i=1dxi2\mathbf{x}\mapsto \sum_{i=1}^d x_i^2x↦∑i=1d​xi2​: the cost of finding the needle in a haystack
Jiefu Zhang
Leonardo Zepeda-Núnez
Xingtai Lv
Lin Lin
101
0
0
24 Feb 2020
Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven
  Exploration
Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven ExplorationNeural Information Processing Systems (NeurIPS), 2020
Cédric Colas
Tristan Karch
Nicolas Lair
Jean-Michel Dussoux
Clément Moulin-Frier
Peter Ford Dominey
Pierre-Yves Oudeyer
LM&RoLLMAGLRM
253
134
0
21 Feb 2020
Stochastic Latent Residual Video Prediction
Stochastic Latent Residual Video PredictionInternational Conference on Machine Learning (ICML), 2020
Jean-Yves Franceschi
E. Delasalles
Mickaël Chen
Sylvain Lamprier
Patrick Gallinari
VGen
410
163
0
21 Feb 2020
Set2Graph: Learning Graphs From Sets
Set2Graph: Learning Graphs From SetsNeural Information Processing Systems (NeurIPS), 2020
Hadar Serviansky
Nimrod Segol
Jonathan Shlomi
Kyle Cranmer
Eilam Gross
Haggai Maron
Y. Lipman
PINNGNN
383
36
0
20 Feb 2020
The Benefits of Pairwise Discriminators for Adversarial Training
The Benefits of Pairwise Discriminators for Adversarial Training
Shangyuan Tong
T. Garipov
Tommi Jaakkola
106
0
0
20 Feb 2020
On Learning Sets of Symmetric Elements
On Learning Sets of Symmetric ElementsInternational Conference on Machine Learning (ICML), 2020
Haggai Maron
Or Litany
Gal Chechik
Ethan Fetaya
364
144
0
20 Feb 2020
TIES: Temporal Interaction Embeddings For Enhancing Social Media
  Integrity At Facebook
TIES: Temporal Interaction Embeddings For Enhancing Social Media Integrity At FacebookKnowledge Discovery and Data Mining (KDD), 2020
Nima Noorshams
Saurabh Verma
A. Hofleitner
146
19
0
18 Feb 2020
A Computationally Efficient Neural Network Invariant to the Action of
  Symmetry Subgroups
A Computationally Efficient Neural Network Invariant to the Action of Symmetry SubgroupsIEEE International Joint Conference on Neural Network (IJCNN), 2020
Piotr Kicki
Mete Ozay
Piotr Skrzypczyñski
88
4
0
18 Feb 2020
Multi-Scale Representation Learning for Spatial Feature Distributions
  using Grid Cells
Multi-Scale Representation Learning for Spatial Feature Distributions using Grid CellsInternational Conference on Learning Representations (ICLR), 2020
Gengchen Mai
K. Janowicz
Bo Yan
Rui Zhu
Ling Cai
Ni Lao
SSL
268
153
0
16 Feb 2020
Monotonic Cardinality Estimation of Similarity Selection: A Deep
  Learning Approach
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach
Yaoshu Wang
Chuan Xiao
Jianbin Qin
Xin Cao
Yifang Sun
Wei Wang
Makoto Onizuka
244
26
0
15 Feb 2020
Query2box: Reasoning over Knowledge Graphs in Vector Space using Box
  Embeddings
Query2box: Reasoning over Knowledge Graphs in Vector Space using Box EmbeddingsInternational Conference on Learning Representations (ICLR), 2020
Hongyu Ren
Weihua Hu
J. Leskovec
272
345
0
14 Feb 2020
A Framework for End-to-End Learning on Semantic Tree-Structured Data
A Framework for End-to-End Learning on Semantic Tree-Structured Data
William Woof
Ke Chen
149
3
0
13 Feb 2020
Explainable Deep Modeling of Tabular Data using TableGraphNet
Explainable Deep Modeling of Tabular Data using TableGraphNet
G. Terejanu
Jawad Chowdhury
Rezaur Rashid
Asif J. Chowdhury
LMTDFAtt
117
3
0
12 Feb 2020
Can Graph Neural Networks Count Substructures?
Can Graph Neural Networks Count Substructures?Neural Information Processing Systems (NeurIPS), 2020
Zhengdao Chen
Lei Chen
Soledad Villar
Joan Bruna
GNN
560
354
0
10 Feb 2020
Hypernetwork approach to generating point clouds
Hypernetwork approach to generating point cloudsInternational Conference on Machine Learning (ICML), 2020
Przemysław Spurek
Sebastian Winczowski
Jacek Tabor
M. Zamorski
Maciej Ziȩba
Tomasz Trzciñski
3DPC
201
35
0
10 Feb 2020
Universal Equivariant Multilayer Perceptrons
Universal Equivariant Multilayer PerceptronsInternational Conference on Machine Learning (ICML), 2020
Siamak Ravanbakhsh
355
55
0
07 Feb 2020
PLLay: Efficient Topological Layer based on Persistence Landscapes
PLLay: Efficient Topological Layer based on Persistence Landscapes
Kwangho Kim
Jisu Kim
Manzil Zaheer
Joon Sik Kim
Frédéric Chazal
Larry A. Wasserman
264
13
0
07 Feb 2020
Message Passing Query Embedding
Message Passing Query Embedding
Daniel Daza
Michael Cochez
GNN
168
8
0
06 Feb 2020
Graph Representation Learning via Graphical Mutual Information
  Maximization
Graph Representation Learning via Graphical Mutual Information MaximizationThe Web Conference (WWW), 2020
Zhen Peng
Wenbing Huang
Minnan Luo
Q. Zheng
Yu Rong
Qifeng Bai
Junzhou Huang
SSL
384
656
0
04 Feb 2020
Convolutional Neural Networks as Summary Statistics for Approximate
  Bayesian Computation
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian ComputationIEEE/ACM Transactions on Computational Biology & Bioinformatics (TCBB), 2020
Mattias Åkesson
Prashant Singh
Fredrik Wrede
Andreas Hellander
BDL
304
38
0
31 Jan 2020
Learn to Predict Sets Using Feed-Forward Neural Networks
Learn to Predict Sets Using Feed-Forward Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
H. Rezatofighi
Tianyu Zhu
Roman Kaskman
F. Motlagh
Javen Qinfeng Shi
Anton Milan
Zorah Lähner
Laura Leal-Taixé
Ian Reid
SSL
299
18
0
30 Jan 2020
Objective Social Choice: Using Auxiliary Information to Improve Voting
  Outcomes
Objective Social Choice: Using Auxiliary Information to Improve Voting OutcomesAdaptive Agents and Multi-Agent Systems (AAMAS), 2020
Silviu Pitis
Michael Ruogu Zhang
79
1
0
27 Jan 2020
TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced
  Graph Neural Network
TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural NetworkThe Web Conference (WWW), 2020
Jiaming Shen
Zhihong Shen
Chenyan Xiong
Chi Wang
Kuansan Wang
Jiawei Han
192
81
0
26 Jan 2020
Graph Ordering: Towards the Optimal by Learning
Graph Ordering: Towards the Optimal by LearningWISE (WISE), 2020
Kangfei Zhao
Yu Rong
Jianwei Yu
Junzhou Huang
Hao Zhang
121
5
0
18 Jan 2020
Understanding the Power of Persistence Pairing via Permutation Test
Understanding the Power of Persistence Pairing via Permutation Test
Chen Cai
Yusu Wang
114
6
0
16 Jan 2020
Stepwise Model Selection for Sequence Prediction via Deep Kernel
  Learning
Stepwise Model Selection for Sequence Prediction via Deep Kernel LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Yao Zhang
Daniel Jarrett
M. Schaar
286
9
0
12 Jan 2020
Retrosynthesis Prediction with Conditional Graph Logic Network
Retrosynthesis Prediction with Conditional Graph Logic NetworkNeural Information Processing Systems (NeurIPS), 2020
H. Dai
Chengtao Li
Connor W. Coley
Bo Dai
Le Song
300
218
0
06 Jan 2020
Representing Unordered Data Using Complex-Weighted Multiset Automata
Representing Unordered Data Using Complex-Weighted Multiset AutomataInternational Conference on Machine Learning (ICML), 2020
Justin DeBenedetto
David Chiang
196
0
0
02 Jan 2020
Histogram Layers for Texture Analysis
Histogram Layers for Texture AnalysisIEEE Transactions on Artificial Intelligence (IEEE TAI), 2020
Joshua Peeples
Weihuang Xu
A. Zare
742
58
0
01 Jan 2020
A Gentle Introduction to Deep Learning for Graphs
A Gentle Introduction to Deep Learning for GraphsNeural Networks (NN), 2019
D. Bacciu
Federico Errica
Alessio Micheli
Marco Podda
AI4CEGNN
261
304
0
29 Dec 2019
Quaternion Equivariant Capsule Networks for 3D Point Clouds
Quaternion Equivariant Capsule Networks for 3D Point CloudsEuropean Conference on Computer Vision (ECCV), 2019
Yongheng Zhao
Tolga Birdal
J. E. Lenssen
Emanuele Menegatti
Leonidas Guibas
Federico Tombari
3DPC
433
92
0
27 Dec 2019
Deep Learning for 3D Point Clouds: A Survey
Deep Learning for 3D Point Clouds: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
Yulan Guo
Hanyun Wang
Qingyong Hu
Hao Liu
Tianpeng Liu
Bennamoun
3DPC
478
2,021
0
27 Dec 2019
Geometry Sharing Network for 3D Point Cloud Classification and
  Segmentation
Geometry Sharing Network for 3D Point Cloud Classification and SegmentationAAAI Conference on Artificial Intelligence (AAAI), 2019
Mingye Xu
Zhipeng Zhou
Yu Qiao
3DPC
161
100
0
23 Dec 2019
A Fair Comparison of Graph Neural Networks for Graph Classification
A Fair Comparison of Graph Neural Networks for Graph ClassificationInternational Conference on Learning Representations (ICLR), 2019
Federico Errica
Marco Podda
D. Bacciu
Alessio Micheli
FaML
383
495
0
20 Dec 2019
Learning Canonical Representations for Scene Graph to Image Generation
Learning Canonical Representations for Scene Graph to Image GenerationEuropean Conference on Computer Vision (ECCV), 2019
Roei Herzig
Amir Bar
Huijuan Xu
Gal Chechik
Trevor Darrell
Amir Globerson
GNNOCL
408
114
0
16 Dec 2019
Coloring graph neural networks for node disambiguation
Coloring graph neural networks for node disambiguationInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
George Dasoulas
Ludovic Dos Santos
Kevin Scaman
Aladin Virmaux
185
86
0
12 Dec 2019
LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices
LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices
R. Rosu
Peer Schütt
Jan Quenzel
Sven Behnke
3DPC3DV
266
99
0
12 Dec 2019
Learned Interpolation for 3D Generation
Learned Interpolation for 3D Generation
Austin Dill
Songwei Ge
Eunsu Kang
Chun-Liang Li
Barnabás Póczós
3DV
88
0
0
08 Dec 2019
Getting Topology and Point Cloud Generation to Mesh
Getting Topology and Point Cloud Generation to Mesh
Austin Dill
Chun-Liang Li
Songwei Ge
Eunsu Kang
3DPC
172
3
0
08 Dec 2019
MetaFun: Meta-Learning with Iterative Functional Updates
MetaFun: Meta-Learning with Iterative Functional UpdatesInternational Conference on Machine Learning (ICML), 2019
Jin Xu
Jean-François Ton
Hyunjik Kim
Adam R. Kosiorek
Yee Whye Teh
343
75
0
05 Dec 2019
Deep Fictitious Play for Finding Markovian Nash Equilibrium in
  Multi-Agent Games
Deep Fictitious Play for Finding Markovian Nash Equilibrium in Multi-Agent GamesMathematical and Scientific Machine Learning (MSML), 2019
Jiequn Han
Ruimeng Hu
102
49
0
04 Dec 2019
Learning Domain-Independent Planning Heuristics with Hypergraph Networks
Learning Domain-Independent Planning Heuristics with Hypergraph NetworksInternational Conference on Automated Planning and Scheduling (ICAPS), 2019
William Shen
Felipe W. Trevizan
Sylvie Thiébaux
194
97
0
29 Nov 2019
Information-Geometric Set Embeddings (IGSE): From Sets to Probability
  Distributions
Information-Geometric Set Embeddings (IGSE): From Sets to Probability Distributions
Ke Sun
Frank Nielsen
GAN
181
4
0
27 Nov 2019
Deep Density: circumventing the Kohn-Sham equations via symmetry
  preserving neural networks
Deep Density: circumventing the Kohn-Sham equations via symmetry preserving neural networksJournal of Computational Physics (JCP), 2019
Leonardo Zepeda-Núnez
Yixiao Chen
Jiefu Zhang
Weile Jia
Linfeng Zhang
Lin Lin
158
37
0
27 Nov 2019
SuperGlue: Learning Feature Matching with Graph Neural Networks
SuperGlue: Learning Feature Matching with Graph Neural NetworksComputer Vision and Pattern Recognition (CVPR), 2019
Paul-Edouard Sarlin
Daniel DeTone
Tomasz Malisiewicz
Andrew Rabinovich
3DPCOffRL
587
2,408
0
26 Nov 2019
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