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1703.06114
Cited By
Deep Sets
10 March 2017
Manzil Zaheer
Satwik Kottur
Siamak Ravanbakhsh
Barnabás Póczós
Ruslan Salakhutdinov
Alex Smola
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Papers citing
"Deep Sets"
50 / 1,441 papers shown
Title
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Yixin Chen
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Muhan Zhang
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Riddhish Bhalodia
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QGNN: Value Function Factorisation with Graph Neural Networks
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Amanda Prorok
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Conditional set generation using Seq2seq models
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Niket Tandon
Yiming Yang
Antoine Bosselut
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10
0
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Convolutional Neural Processes for Inpainting Satellite Images
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M. Bakler
D. Guo
Hamzah Hashim
Martin Ignatov
Harrison Zhu
32
8
0
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Efficient anti-symmetrization of a neural network layer by taming the sign problem
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Learning to Assemble Geometric Shapes
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Jungtaek Kim
H. Chung
Jaesik Park
Minsu Cho
23
4
0
24 May 2022
High-Order Pooling for Graph Neural Networks with Tensor Decomposition
Chenqing Hua
Guillaume Rabusseau
Jian Tang
81
25
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Variable-Input Deep Operator Networks
Michael Prasthofer
Tim De Ryck
Siddhartha Mishra
53
23
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23 May 2022
Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited
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Equivariant Mesh Attention Networks
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Jose Gallego-Posada
Francesco Vigano
J. Rowbottom
Taco S. Cohen
3DPC
MDE
AI4CE
59
10
0
21 May 2022
eBIM-GNN : Fast and Scalable energy analysis through BIMs and Graph Neural Networks
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Annada Prasad Behera
Subhankar Mishra
AI4CE
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R. Patel
Elias Boutros Khalil
Merve Bodur
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0
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Towards Understanding Grokking: An Effective Theory of Representation Learning
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O. Kitouni
Niklas Nolte
Eric J. Michaud
Max Tegmark
Mike Williams
AI4CE
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Set-based Meta-Interpolation for Few-Task Meta-Learning
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Bruno Andreis
Kenji Kawaguchi
Juho Lee
Sung Ju Hwang
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Lessons Learned: Defending Against Property Inference Attacks
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Jens Wettlaufer
Daniel Demmler
Hannes Federrath
AAML
41
1
0
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What is an equivariant neural network?
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Bradley J. Nelson
BDL
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MLT
37
22
0
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Asking for Knowledge: Training RL Agents to Query External Knowledge Using Language
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Xingdi Yuan
Marc-Alexandre Côté
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Alex Schwing
RALM
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Low Dimensional Invariant Embeddings for Universal Geometric Learning
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S. Gortler
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TartanDrive: A Large-Scale Dataset for Learning Off-Road Dynamics Models
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Matthew Sivaprakasam
Sean J. Wang
Wenshan Wang
Aaron M. Johnson
Sebastian Scherer
35
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IRC-safe Graph Autoencoder for unsupervised anomaly detection
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Akanksha Bhardwaj
C. Englert
P. Konar
Vishal S. Ngairangbam
M. Spannowsky
34
26
0
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Visual Attention Methods in Deep Learning: An In-Depth Survey
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Saeed Anwar
Ibrahim Radwan
Fahad Shahbaz Khan
Ajmal Mian
34
147
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Theory of Graph Neural Networks: Representation and Learning
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38
68
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Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation
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Bruno Vallet
Loic Landrieu
3DPC
31
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Relaxing Equivariance Constraints with Non-stationary Continuous Filters
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David W. Romero
Mark van der Wilk
29
33
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35
4
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Neural Processes with Stochastic Attention: Paying more attention to the context dataset
Mingyu Kim
Kyeongryeol Go
Se-Young Yun
40
20
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Learning Object-Centered Autotelic Behaviors with Graph Neural Networks
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Olivier Sigaud
40
0
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Identifying Ambiguous Similarity Conditions via Semantic Matching
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Yi Shi
De-Chuan Zhan
CoGe
36
7
0
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Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition
Axel Berg
Magnus Oskarsson
Mark O'Connor
3DPC
ViT
29
26
0
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Equivariance Discovery by Learned Parameter-Sharing
Raymond A. Yeh
Yuan-Ting Hu
M. Hasegawa-Johnson
Alex Schwing
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42
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Few-Shot Forecasting of Time-Series with Heterogeneous Channels
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Rafael Rêgo Drumond
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The Self-Optimal-Transport Feature Transform
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Domain Adversarial Graph Convolutional Network Based on RSSI and Crowdsensing for Indoor Localization
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Xuan Song
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Rinon Gal
E. Meirom
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Yuval Atzmon
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56
83
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Matching Feature Sets for Few-Shot Image Classification
Arman Afrasiyabi
Hugo Larochelle
Jean-François Lalonde
Christian Gagné
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3D Equivariant Graph Implicit Functions
Yunlu Chen
Basura Fernando
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E. Gavves
3DPC
32
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Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks
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When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
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Sungyong Seo
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Neural Face Video Compression using Multiple Views
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Stefan Brugger
Ali Benlalah
Sebastian Martin
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14
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MatchNorm: Learning-based Point Cloud Registration for 6D Object Pose Estimation in the Real World
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Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges
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G. Chachamis
G. Dezoort
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44
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Graph Neural Networks for Wireless Communications: From Theory to Practice
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Shenghui Song
Khaled B. Letaief
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CrossBeam: Learning to Search in Bottom-Up Program Synthesis
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Kevin Ellis
Charles Sutton
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11
24
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Graph Representation Learning with Individualization and Refinement
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W. Lee
22
2
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Practical Conditional Neural Processes Via Tractable Dependent Predictions
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James Requeima
W. Bruinsma
Anna Vaughan
Richard Turner
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36
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Arash Behboodi
Joseph B. Soriaga
Max Welling
Roohollah Amiri
S. Yerramalli
Taesang Yoo
22
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Incorporating Heterophily into Graph Neural Networks for Graph Classification
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Sourav Medya
Wei Ye
38
4
0
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Permutation Invariant Representations with Applications to Graph Deep Learning
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M. Singh
31
25
0
14 Mar 2022
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