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How Neural Networks Extrapolate: From Feedforward to Graph Neural
  Networks
v1v2v3v4v5 (latest)

How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks

International Conference on Learning Representations (ICLR), 2020
24 September 2020
Keyulu Xu
Mozhi Zhang
Jingling Li
S. Du
Ken-ichi Kawarabayashi
Stefanie Jegelka
    MLT
ArXiv (abs)PDFHTML

Papers citing "How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks"

46 / 196 papers shown
On Provable Benefits of Depth in Training Graph Convolutional Networks
On Provable Benefits of Depth in Training Graph Convolutional NetworksNeural Information Processing Systems (NeurIPS), 2021
Weilin Cong
M. Ramezani
M. Mahdavi
186
89
0
28 Oct 2021
How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A
  Semantic Evidence View
How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A Semantic Evidence ViewAAAI Conference on Artificial Intelligence (AAAI), 2021
Ren Li
Yanan Cao
Qiannan Zhu
Guanqun Bi
Fang Fang
Yi Liu
Qian Li
255
91
0
24 Sep 2021
Implicit Behavioral Cloning
Implicit Behavioral CloningConference on Robot Learning (CoRL), 2021
Peter R. Florence
Corey Lynch
Andy Zeng
Oscar Ramirez
Ayzaan Wahid
Laura Downs
Adrian S. Wong
Johnny Lee
Igor Mordatch
Jonathan Tompson
OffRL
493
532
0
01 Sep 2021
How Powerful is Graph Convolution for Recommendation?
How Powerful is Graph Convolution for Recommendation?
Yifei Shen
Yongji Wu
Yao Zhang
Caihua Shan
Jun Zhang
Khaled B. Letaief
Dongsheng Li
GNN
240
121
0
17 Aug 2021
Model architecture can transform catastrophic forgetting into positive
  transfer
Model architecture can transform catastrophic forgetting into positive transferScientific Reports (Sci Rep), 2021
M. Ruíz-García
144
6
0
09 Aug 2021
Reasoning-Modulated Representations
Reasoning-Modulated RepresentationsLOG IN (LOG IN), 2021
Petar Velivcković
Matko Bovsnjak
Thomas Kipf
Alexander Lerchner
R. Hadsell
Razvan Pascanu
Charles Blundell
OCLOODSSL
294
16
0
19 Jul 2021
Deep Extrapolation for Attribute-Enhanced Generation
Deep Extrapolation for Attribute-Enhanced Generation
Alvin Chan
Ali Madani
Ben Krause
Nikhil Naik
220
30
0
07 Jul 2021
A Theoretical Analysis of Fine-tuning with Linear Teachers
A Theoretical Analysis of Fine-tuning with Linear Teachers
Gal Shachaf
Alon Brutzkus
Amir Globerson
218
17
0
04 Jul 2021
Pre-Trained Models: Past, Present and Future
Pre-Trained Models: Past, Present and FutureAI Open (AO), 2021
Xu Han
Zhengyan Zhang
Ning Ding
Yuxian Gu
Xiao Liu
...
Jie Tang
Ji-Rong Wen
Jinhui Yuan
Wayne Xin Zhao
Jun Zhu
AIFinMQAI4MH
387
995
0
14 Jun 2021
Learning to Pool in Graph Neural Networks for Extrapolation
Learning to Pool in Graph Neural Networks for Extrapolation
Jihoon Ko
Taehyung Kwon
Kijung Shin
Juho Lee
132
6
0
11 Jun 2021
What training reveals about neural network complexity
What training reveals about neural network complexityNeural Information Processing Systems (NeurIPS), 2021
Andreas Loukas
Marinos Poiitis
Stefanie Jegelka
247
12
0
08 Jun 2021
Understand and Improve Contrastive Learning Methods for Visual
  Representation: A Review
Understand and Improve Contrastive Learning Methods for Visual Representation: A Review
Ran Liu
SSL
139
12
0
06 Jun 2021
Out-of-Distribution Generalization in Kernel Regression
Out-of-Distribution Generalization in Kernel RegressionNeural Information Processing Systems (NeurIPS), 2021
Abdulkadir Canatar
Blake Bordelon
Cengiz Pehlevan
OODDOOD
202
21
0
04 Jun 2021
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement
  Learning
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2021
Mingde Zhao
Zhen Liu
Sitao Luan
Shuyuan Zhang
Doina Precup
Yoshua Bengio
453
40
0
03 Jun 2021
Neural Trees for Learning on Graphs
Neural Trees for Learning on GraphsNeural Information Processing Systems (NeurIPS), 2021
Rajat Talak
Siyi Hu
Lisa Peng
Luca Carlone
274
27
0
15 May 2021
Optimization of Graph Neural Networks: Implicit Acceleration by Skip
  Connections and More Depth
Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More DepthInternational Conference on Machine Learning (ICML), 2021
Keyulu Xu
Mozhi Zhang
Stefanie Jegelka
Kenji Kawaguchi
GNN
246
85
0
10 May 2021
GANTL: Towards Practical and Real-Time Topology Optimization with
  Conditional GANs and Transfer Learning
GANTL: Towards Practical and Real-Time Topology Optimization with Conditional GANs and Transfer Learning
M. Behzadi
H. Ilies
AI4CE
174
18
0
07 May 2021
Data-driven Full-waveform Inversion Surrogate using Conditional
  Generative Adversarial Networks
Data-driven Full-waveform Inversion Surrogate using Conditional Generative Adversarial NetworksIEEE International Joint Conference on Neural Network (IJCNN), 2021
Marcus Saraiva
Avelino Forechi
Jorcy de Oliveira Neto
A. DelRey
T. Rauber
133
9
0
30 Apr 2021
Neural Networks for Learning Counterfactual G-Invariances from Single
  Environments
Neural Networks for Learning Counterfactual G-Invariances from Single EnvironmentsInternational Conference on Learning Representations (ICLR), 2021
S Chandra Mouli
Bruno Ribeiro
OOD
189
13
0
20 Apr 2021
Domain Generalization with MixStyle
Domain Generalization with MixStyleInternational Conference on Learning Representations (ICLR), 2021
Kaiyang Zhou
Yongxin Yang
Yu Qiao
Tao Xiang
331
916
0
05 Apr 2021
Decentralized Statistical Inference with Unrolled Graph Neural Networks
Decentralized Statistical Inference with Unrolled Graph Neural NetworksIEEE Conference on Decision and Control (CDC), 2021
He Wang
Yifei Shen
Ziyuan Wang
Dongsheng Li
Jun Zhang
Khaled B. Letaief
Jie Lu
FedML
119
6
0
04 Apr 2021
On the Equivalence Between Temporal and Static Graph Representations for
  Observational Predictions
On the Equivalence Between Temporal and Static Graph Representations for Observational Predictions
Jianfei Gao
Bruno Ribeiro
267
19
0
12 Mar 2021
Size-Invariant Graph Representations for Graph Classification
  Extrapolations
Size-Invariant Graph Representations for Graph Classification ExtrapolationsInternational Conference on Machine Learning (ICML), 2021
Beatrice Bevilacqua
Yangze Zhou
Bruno Ribeiro
OOD
355
121
0
08 Mar 2021
Domain Generalization: A Survey
Domain Generalization: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Kaiyang Zhou
Ziwei Liu
Yu Qiao
Tao Xiang
Chen Change Loy
OODAI4CE
840
1,336
0
03 Mar 2021
Towards Deepening Graph Neural Networks: A GNTK-based Optimization
  Perspective
Towards Deepening Graph Neural Networks: A GNTK-based Optimization PerspectiveInternational Conference on Learning Representations (ICLR), 2021
Wei Huang
Yayong Li
Weitao Du
Jie Yin
R. Xu
Ling-Hao Chen
Miao Zhang
208
19
0
03 Mar 2021
Uncertainty Quantification by Ensemble Learning for Computational
  Optical Form Measurements
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements
L. Hoffmann
I. Fortmeier
Clemens Elster
UQCV
167
35
0
01 Mar 2021
Persistent Message Passing
Persistent Message Passing
Heiko Strathmann
M. Barekatain
Charles Blundell
Petar Velickovic
231
16
0
01 Mar 2021
Abelian Neural Networks
Abelian Neural Networks
Kenshi Abe
Takanori Maehara
Issei Sato
148
2
0
24 Feb 2021
A Theory of Label Propagation for Subpopulation Shift
A Theory of Label Propagation for Subpopulation ShiftInternational Conference on Machine Learning (ICML), 2021
Tianle Cai
Ruiqi Gao
Jason D. Lee
Qi Lei
267
55
0
22 Feb 2021
Combinatorial optimization and reasoning with graph neural networks
Combinatorial optimization and reasoning with graph neural networksInternational Joint Conference on Artificial Intelligence (IJCAI), 2021
Quentin Cappart
Didier Chételat
Elias Boutros Khalil
Andrea Lodi
Christopher Morris
Petar Velickovic
AI4CE
479
437
0
18 Feb 2021
Differentiable sampling of molecular geometries with uncertainty-based
  adversarial attacks
Differentiable sampling of molecular geometries with uncertainty-based adversarial attacksNature Communications (Nat Commun), 2021
Daniel Schwalbe-Koda
Aik Rui Tan
Rafael Gómez-Bombarelli
AAML
322
72
0
27 Jan 2021
Deep Learning Generalization and the Convex Hull of Training Sets
Deep Learning Generalization and the Convex Hull of Training Sets
Roozbeh Yousefzadeh
148
21
0
25 Jan 2021
Contrastive Behavioral Similarity Embeddings for Generalization in
  Reinforcement Learning
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2021
Rishabh Agarwal
Marlos C. Machado
Pablo Samuel Castro
Marc G. Bellemare
OffRL
345
184
0
13 Jan 2021
How Does a Neural Network's Architecture Impact Its Robustness to Noisy
  Labels?
How Does a Neural Network's Architecture Impact Its Robustness to Noisy Labels?Neural Information Processing Systems (NeurIPS), 2020
Jingling Li
Mozhi Zhang
Keyulu Xu
John P. Dickerson
Jimmy Ba
OODNoLa
301
22
0
23 Dec 2020
Learning Canonical Transformations
Learning Canonical Transformations
Zachary Dulberg
Jonathan Cohen
142
1
0
17 Nov 2020
Probing Predictions on OOD Images via Nearest Categories
Probing Predictions on OOD Images via Nearest Categories
Yao-Yuan Yang
Cyrus Rashtchian
Ruslan Salakhutdinov
Kamalika Chaudhuri
AAML
410
0
0
17 Nov 2020
On the equivalence of molecular graph convolution and molecular wave
  function with poor basis set
On the equivalence of molecular graph convolution and molecular wave function with poor basis setNeural Information Processing Systems (NeurIPS), 2020
Masashi Tsubaki
T. Mizoguchi
103
10
0
16 Nov 2020
Empirical or Invariant Risk Minimization? A Sample Complexity
  Perspective
Empirical or Invariant Risk Minimization? A Sample Complexity PerspectiveInternational Conference on Learning Representations (ICLR), 2020
Kartik Ahuja
Jun Wang
Amit Dhurandhar
Karthikeyan Shanmugam
Kush R. Varshney
OOD
273
83
0
30 Oct 2020
From Local Structures to Size Generalization in Graph Neural Networks
From Local Structures to Size Generalization in Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2020
Gilad Yehudai
Ethan Fetaya
E. Meirom
Gal Chechik
Haggai Maron
GNNAI4CE
501
159
0
17 Oct 2020
The Risks of Invariant Risk Minimization
The Risks of Invariant Risk Minimization
Elan Rosenfeld
Pradeep Ravikumar
Andrej Risteski
OOD
403
342
0
12 Oct 2020
Information Obfuscation of Graph Neural Networks
Information Obfuscation of Graph Neural Networks
Peiyuan Liao
Han Zhao
Keyulu Xu
Tommi Jaakkola
Geoffrey J. Gordon
Stefanie Jegelka
Ruslan Salakhutdinov
AAML
280
37
0
28 Sep 2020
GraphNorm: A Principled Approach to Accelerating Graph Neural Network
  Training
GraphNorm: A Principled Approach to Accelerating Graph Neural Network TrainingInternational Conference on Machine Learning (ICML), 2020
Tianle Cai
Shengjie Luo
Keyulu Xu
Di He
Tie-Yan Liu
Liwei Wang
GNN
272
202
0
07 Sep 2020
Self-supervised Learning: Generative or Contrastive
Self-supervised Learning: Generative or Contrastive
Xiao Liu
Fanjin Zhang
Zhenyu Hou
Zhaoyu Wang
Li Mian
Jing Zhang
Jie Tang
SSL
640
2,001
0
15 Jun 2020
Learning the Travelling Salesperson Problem Requires Rethinking
  Generalization
Learning the Travelling Salesperson Problem Requires Rethinking Generalization
Chaitanya K. Joshi
Quentin Cappart
Louis-Martin Rousseau
T. Laurent
744
149
0
12 Jun 2020
Neural Status Registers
Neural Status RegistersInternational Conference on Machine Learning (ICML), 2020
Lukas Faber
Roger Wattenhofer
139
9
0
15 Apr 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Out-of-Distribution Generalization via Risk Extrapolation (REx)International Conference on Machine Learning (ICML), 2020
David M. Krueger
Ethan Caballero
J. Jacobsen
Amy Zhang
Jonathan Binas
Dinghuai Zhang
Rémi Le Priol
Aaron Courville
OOD
933
1,099
0
02 Mar 2020
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