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What Can Neural Networks Reason About?

What Can Neural Networks Reason About?

30 May 2019
Keyulu Xu
Jingling Li
Mozhi Zhang
S. Du
Ken-ichi Kawarabayashi
Stefanie Jegelka
    NAI
    AI4CE
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Papers citing "What Can Neural Networks Reason About?"

50 / 54 papers shown
Title
RICA2: Rubric-Informed, Calibrated Assessment of Actions
RICA2: Rubric-Informed, Calibrated Assessment of Actions
Abrar Majeedi
Viswanatha Reddy Gajjala
Satya Sai Srinath Namburi Gnvv
Yin Li
CML
28
2
0
04 Aug 2024
The CLRS-Text Algorithmic Reasoning Language Benchmark
The CLRS-Text Algorithmic Reasoning Language Benchmark
Larisa Markeeva
Sean McLeish
Borja Ibarz
Wilfried Bounsi
Olga Kozlova
Alex Vitvitskyi
Charles Blundell
Tom Goldstein
Avi Schwarzschild
Petar Veličković
LRM
36
12
0
06 Jun 2024
A Short Review on Novel Approaches for Maximum Clique Problem: from
  Classical algorithms to Graph Neural Networks and Quantum algorithms
A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms
Raffaele Marino
L. Buffoni
Bogdan Zavalnij
GNN
34
5
0
13 Mar 2024
Relational Deep Learning: Graph Representation Learning on Relational
  Databases
Relational Deep Learning: Graph Representation Learning on Relational Databases
Matthias Fey
Weihua Hu
Kexin Huang
J. E. Lenssen
Rishabh Ranjan
Joshua Robinson
Rex Ying
Jiaxuan You
J. Leskovec
GNN
40
30
0
07 Dec 2023
E(2)-Equivariant Graph Planning for Navigation
E(2)-Equivariant Graph Planning for Navigation
Linfeng Zhao
Hongyu Li
T. Padır
Huaizu Jiang
Lawson L. S. Wong
25
6
0
22 Sep 2023
The Expressive Power of Graph Neural Networks: A Survey
The Expressive Power of Graph Neural Networks: A Survey
Bingxue Zhang
Changjun Fan
Shixuan Liu
Kuihua Huang
Xiang Zhao
Jin-Yu Huang
Zhong Liu
40
19
0
16 Aug 2023
Can Euclidean Symmetry be Leveraged in Reinforcement Learning and
  Planning?
Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?
Linfeng Zhao
Owen Howell
Jung Yeon Park
Xu Zhu
Robin G. Walters
Lawson L. S. Wong
36
1
0
17 Jul 2023
Neural Algorithmic Reasoning Without Intermediate Supervision
Neural Algorithmic Reasoning Without Intermediate Supervision
Gleb Rodionov
Liudmila Prokhorenkova
OffRL
LRM
OOD
24
10
0
23 Jun 2023
On the Relationships between Graph Neural Networks for the Simulation of
  Physical Systems and Classical Numerical Methods
On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods
Artur P. Toshev
Ludger Paehler
A. Panizza
Nikolaus A. Adams
AI4CE
PINN
11
5
0
31 Mar 2023
Neural Algorithmic Reasoning with Causal Regularisation
Neural Algorithmic Reasoning with Causal Regularisation
Beatrice Bevilacqua
Kyriacos Nikiforou
Borja Ibarz
Ioana Bica
Michela Paganini
Charles Blundell
Jovana Mitrović
Petar Velivcković
OOD
CML
NAI
36
26
0
20 Feb 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on
  Graph Diffusion
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
Haotian Ju
Dongyue Li
Aneesh Sharma
Hongyang R. Zhang
28
40
0
09 Feb 2023
Graph Neural Networks can Recover the Hidden Features Solely from the
  Graph Structure
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure
Ryoma Sato
31
5
0
26 Jan 2023
Flex-Net: A Graph Neural Network Approach to Resource Management in
  Flexible Duplex Networks
Flex-Net: A Graph Neural Network Approach to Resource Management in Flexible Duplex Networks
Tharaka Perera
S. Atapattu
Yuting Fang
Prathapasinghe Dharmawansa
J. Evans
GNN
25
4
0
20 Jan 2023
Learnable Commutative Monoids for Graph Neural Networks
Learnable Commutative Monoids for Graph Neural Networks
Euan Ong
Petar Velickovic
10
12
0
16 Dec 2022
PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers
  using Synthetic Scene Data
PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data
Roei Herzig
Ofir Abramovich
Elad Ben-Avraham
Assaf Arbelle
Leonid Karlinsky
Ariel Shamir
Trevor Darrell
Amir Globerson
34
16
0
08 Dec 2022
Continuous Neural Algorithmic Planners
Continuous Neural Algorithmic Planners
Yu He
Petar Velivcković
Pietro Lio'
Andreea Deac
24
5
0
29 Nov 2022
A Scalable Graph Neural Network Decoder for Short Block Codes
A Scalable Graph Neural Network Decoder for Short Block Codes
Kou Tian
Chentao Yue
Changyang She
Yonghui Li
B. Vucetic
9
4
0
13 Nov 2022
Reducing Collision Checking for Sampling-Based Motion Planning Using
  Graph Neural Networks
Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks
Chen-Ping Yu
Sicun Gao
26
47
0
17 Oct 2022
Provably expressive temporal graph networks
Provably expressive temporal graph networks
Amauri Souza
Diego Mesquita
Samuel Kaski
Vikas K. Garg
89
54
0
29 Sep 2022
On the visual analytic intelligence of neural networks
On the visual analytic intelligence of neural networks
Stanislaw Wo'zniak
Hlynur Jónsson
G. Cherubini
A. Pantazi
E. Eleftheriou
22
0
0
28 Sep 2022
The CLRS Algorithmic Reasoning Benchmark
The CLRS Algorithmic Reasoning Benchmark
Petar Velivcković
Adria Puigdomenech Badia
David Budden
Razvan Pascanu
Andrea Banino
Mikhail Dashevskiy
R. Hadsell
Charles Blundell
161
87
0
31 May 2022
FairNorm: Fair and Fast Graph Neural Network Training
FairNorm: Fair and Fast Graph Neural Network Training
Öykü Deniz Köse
Yanning Shen
AI4CE
13
4
0
20 May 2022
Theory of Graph Neural Networks: Representation and Learning
Theory of Graph Neural Networks: Representation and Learning
Stefanie Jegelka
GNN
AI4CE
33
68
0
16 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed
  Machine Learning
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
Chuizheng Meng
Sungyong Seo
Defu Cao
Sam Griesemer
Yan Liu
PINN
AI4CE
36
55
0
31 Mar 2022
Graph Neural Networks are Dynamic Programmers
Graph Neural Networks are Dynamic Programmers
Andrew Dudzik
Petar Velickovic
28
63
0
29 Mar 2022
Graph Neural Networks for Wireless Communications: From Theory to
  Practice
Graph Neural Networks for Wireless Communications: From Theory to Practice
Yifei Shen
Jun Zhang
Shenghui Song
Khaled B. Letaief
GNN
AI4CE
25
110
0
21 Mar 2022
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs
Zehao Dong
Muhan Zhang
Fuhai Li
Yixin Chen
CML
GNN
33
17
0
19 Mar 2022
Differential equation and probability inspired graph neural networks for latent variable learning
Differential equation and probability inspired graph neural networks for latent variable learning
Zhuangwei Shi
14
3
0
28 Feb 2022
Sign and Basis Invariant Networks for Spectral Graph Representation
  Learning
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Derek Lim
Joshua Robinson
Lingxiao Zhao
Tess E. Smidt
S. Sra
Haggai Maron
Stefanie Jegelka
43
141
0
25 Feb 2022
A Note on Machine Learning Approach for Computational Imaging
A Note on Machine Learning Approach for Computational Imaging
Bin Dong
20
0
0
24 Feb 2022
On Provable Benefits of Depth in Training Graph Convolutional Networks
On Provable Benefits of Depth in Training Graph Convolutional Networks
Weilin Cong
M. Ramezani
M. Mahdavi
24
73
0
28 Oct 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using
  Vector Quantization
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
Mucong Ding
Kezhi Kong
Jingling Li
Chen Zhu
John P. Dickerson
Furong Huang
Tom Goldstein
GNN
MQ
27
47
0
27 Oct 2021
Object-Region Video Transformers
Object-Region Video Transformers
Roei Herzig
Elad Ben-Avraham
K. Mangalam
Amir Bar
Gal Chechik
Anna Rohrbach
Trevor Darrell
Amir Globerson
ViT
21
82
0
13 Oct 2021
Unsupervised Abstract Reasoning for Raven's Problem Matrices
Unsupervised Abstract Reasoning for Raven's Problem Matrices
Tao Zhuo
Qian Huang
Mohan S. Kankanhalli
LRM
113
22
0
21 Sep 2021
Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks
Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks
Dylan Sandfelder
Priyesh Vijayan
William L. Hamilton
14
26
0
22 Jul 2021
Sampling methods for efficient training of graph convolutional networks:
  A survey
Sampling methods for efficient training of graph convolutional networks: A survey
Xin Liu
Mingyu Yan
Lei Deng
Guoqi Li
Xiaochun Ye
Dongrui Fan
GNN
23
100
0
10 Mar 2021
Persistent Message Passing
Persistent Message Passing
Heiko Strathmann
M. Barekatain
Charles Blundell
Petar Velickovic
30
15
0
01 Mar 2021
Combinatorial optimization and reasoning with graph neural networks
Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart
Didier Chételat
Elias Boutros Khalil
Andrea Lodi
Christopher Morris
Petar Velickovic
AI4CE
32
346
0
18 Feb 2021
Graph Neural Networks: Taxonomy, Advances and Trends
Graph Neural Networks: Taxonomy, Advances and Trends
Yu Zhou
Haixia Zheng
Xin Huang
Shufeng Hao
Dengao Li
Jumin Zhao
AI4TS
25
115
0
16 Dec 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
15
34
0
28 Sep 2020
GraphNorm: A Principled Approach to Accelerating Graph Neural Network
  Training
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai
Shengjie Luo
Keyulu Xu
Di He
Tie-Yan Liu
Liwei Wang
GNN
16
158
0
07 Sep 2020
Learning to plan with uncertain topological maps
Learning to plan with uncertain topological maps
E. Beeching
J. Dibangoye
Olivier Simonin
Christian Wolf
19
40
0
10 Jul 2020
Symbolic Logic meets Machine Learning: A Brief Survey in Infinite
  Domains
Symbolic Logic meets Machine Learning: A Brief Survey in Infinite Domains
Vaishak Belle
NAI
LRM
12
36
0
15 Jun 2020
Global Attention Improves Graph Networks Generalization
Global Attention Improves Graph Networks Generalization
Omri Puny
Heli Ben-Hamu
Y. Lipman
27
22
0
14 Jun 2020
Dynamic Language Binding in Relational Visual Reasoning
Dynamic Language Binding in Relational Visual Reasoning
T. Le
Vuong Le
Svetha Venkatesh
T. Tran
NAI
23
19
0
30 Apr 2020
Principal Neighbourhood Aggregation for Graph Nets
Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso
Luca Cavalleri
Dominique Beaini
Pietro Lió
Petar Velickovic
GNN
15
649
0
12 Apr 2020
It's Not What Machines Can Learn, It's What We Cannot Teach
It's Not What Machines Can Learn, It's What We Cannot Teach
Gal Yehuda
Moshe Gabel
Assaf Schuster
FaML
8
37
0
21 Feb 2020
Neural Subgraph Isomorphism Counting
Neural Subgraph Isomorphism Counting
Xin Liu
Haojie Pan
Mutian He
Yangqiu Song
Xin Jiang
Lifeng Shang
GNN
22
78
0
25 Dec 2019
On the Equivalence between Positional Node Embeddings and Structural
  Graph Representations
On the Equivalence between Positional Node Embeddings and Structural Graph Representations
Balasubramaniam Srinivasan
Bruno Ribeiro
17
27
0
01 Oct 2019
Representation Learning on Graphs with Jumping Knowledge Networks
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
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