What Can Neural Networks Reason About?

30 May 2019

Ken-ichi Kawarabayashi

Papers citing "What Can Neural Networks Reason About?"

50 / 51 papers shown

Title
RICA2: Rubric-Informed, Calibrated Assessment of Actions Abrar Majeedi Viswanatha Reddy Gajjala Satya Sai Srinath Namburi Gnvv Yin Li CML 26 2 0 04 Aug 2024
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 34 12 0 06 Jun 2024
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 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 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? 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 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 Artur P. Toshev Ludger Paehler A. Panizza Nikolaus A. Adams AI4CE PINN 11 5 0 31 Mar 2023
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 Haotian Ju Dongyue Li Aneesh Sharma Hongyang R. Zhang 23 40 0 09 Feb 2023
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 Tharaka Perera S. Atapattu Yuting Fang Prathapasinghe Dharmawansa J. Evans GNN 25 4 0 20 Jan 2023
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 Yu He Petar Velivcković Pietro Lio' Andreea Deac 24 5 0 29 Nov 2022
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 Chen-Ping Yu Sicun Gao 24 47 0 17 Oct 2022
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 Stanislaw Wo'zniak Hlynur Jónsson G. Cherubini A. Pantazi E. Eleftheriou 16 0 0 28 Sep 2022
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 Öykü Deniz Köse Yanning Shen AI4CE 11 4 0 20 May 2022
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 Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 34 55 0 31 Mar 2022
Graph Neural Networks are Dynamic Programmers Andrew Dudzik Petar Velickovic 28 62 0 29 Mar 2022
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 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 Zhuangwei Shi 14 3 0 28 Feb 2022
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 40 139 0 25 Feb 2022
A Note on Machine Learning Approach for Computational Imaging Bin Dong 14 0 0 24 Feb 2022
On Provable Benefits of Depth in Training Graph Convolutional Networks Weilin Cong M. Ramezani M. Mahdavi 19 73 0 28 Oct 2021
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 25 47 0 27 Oct 2021
Object-Region Video Transformers Roei Herzig Elad Ben-Avraham K. Mangalam Amir Bar Gal Chechik Anna Rohrbach Trevor Darrell Amir Globerson ViT 19 82 0 13 Oct 2021
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 Xin Liu Mingyu Yan Lei Deng Guoqi Li Xiaochun Ye Dongrui Fan GNN 21 100 0 10 Mar 2021
Persistent Message Passing Heiko Strathmann M. Barekatain Charles Blundell Petar Velickovic 25 15 0 01 Mar 2021
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 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 Peiyuan Liao Han Zhao Keyulu Xu Tommi Jaakkola Geoffrey J. Gordon Stefanie Jegelka Ruslan Salakhutdinov AAML 12 34 0 28 Sep 2020
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 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 Vaishak Belle NAI LRM 10 36 0 15 Jun 2020
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 T. Le Vuong Le Svetha Venkatesh T. Tran NAI 20 19 0 30 Apr 2020
Principal Neighbourhood Aggregation for Graph Nets Gabriele Corso Luca Cavalleri Dominique Beaini Pietro Lió Petar Velickovic GNN 13 649 0 12 Apr 2020
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 Xin Liu Haojie Pan Mutian He Yangqiu Song Xin Jiang Lifeng Shang GNN 20 78 0 25 Dec 2019
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 Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,944 0 09 Jun 2018
Building machines that adapt and compute like brains Brenden Lake J. Tenenbaum AI4CE FedML NAI AILaw 254 890 0 11 Nov 2017
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 241 438 0 01 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 278 1,400 0 01 Dec 2016