ICLR，全称为「International Conference on Learning Representations」（国际学习表征会议），ICLR 是由位列深度学习三大巨头之二的 Yoshua Bengio 和 Yann LeCun 牵头创办，2013 年开始每年举办一次。众所周知，数据的应用表征对于机器学习的性能有着重要影响。表征学习的迅猛发展也伴随着不少问题，比如我们如何更好地从数据中学习更具含义及有效的表征。ICLR对这个领域展开了探索，包括了深度学习、表征学习、度量学习、核学习、组合模型、非常线性结构预测及非凸优化等问题。该会议已经得到学术研究者们的广泛认可，被认为是深度学习领域的顶级会议。
图学习的基准和基线
论文标题：Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation
作者团队：Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah
论文标题：Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions
作者团队： Leslie O’Bray, Max Horn, Bastian Rieck, Karsten Borgwardt
论文标题：GNN is a Counter? Revisiting GNN for Question Answering
作者团队： Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, Tao Qin
论文标题：Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework
作者团队：Xu Ma, Can Qin, Haoxuan You, Haoxi Ran, Yun Fu
GNN理论
论文标题：A New Perspective on “How Graph Neural Networks Go Beyond Weisfeiler-Lehman?”
作者团队：Asiri Wijesinghe, Qing Wang
论文标题：Frame Averaging for Invariant and Equivariant Network Design
作者团队：Omri Puny, Matan Atzmon, Edward J. Smith, Ishan Misra, Aditya Grover, Heli Ben-Hamu, Yaron Lipman
论文标题：Equivariant Subgraph Aggregation Networks
作者团队：Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
论文标题：Understanding over-squashing and bottlenecks on graphs via curvature
作者团队：Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
论文标题：Expressiveness and Approximation Properties of Graph Neural Networks
作者团队：Floris Geerts, Juan L Reutter
论文标题：How Attentive are Graph Attention Networks?
作者团队：Shaked Brody, Uri Alon, Eran Yahav
论文标题：From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness
作者团队：Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
论文标题：Is Homophily a Necessity for Graph Neural Networks?
作者团队：Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang
论文标题：PF-GNN: Differentiable particle filtering based approximation of universal graph representations
作者团队：Mohammed Haroon Dupty, Yanfei Dong, Wee Sun Lee
论文标题：Do We Need Anisotropic Graph Neural Networks?
作者团队：Shyam A. Tailor, Felix Opolka, Pietro Lio, Nicholas Donald Lane
论文标题：LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL
作者团队：Wei Lu
论文标题：Triangle and Four Cycle Counting with Predictions in Graph Streams
作者团队：Justin Y Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David Woodruff, Michael Zhang
论文标题：Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks
作者团队： Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li
论文标题：Why Propagate Alone? Parallel Use of Labels and Features on Graphs Yangkun Wang, Jiarui Jin, Weinan Zhang, Yang Yongyi, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
论文标题：You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks
作者团队：Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic
论文标题：Revisiting Over-smoothing in BERT from the Perspective of Graph
作者团队：Han Shi, JIAHUI GAO, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James Kwok
新的GNN架构
论文标题：Neural Structured Prediction for Inductive Node Classification
作者团队：Meng Qu, Huiyu Cai, Jian Tang
论文标题：Geometric and Physical Quantities improve E(3) Equivariant Message Passing
作者团队：Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J Bekkers, Max Welling
论文标题：Topological Graph Neural Networks
作者团队： Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten Borgwardt
论文标题：GRAND++: Graph Neural Diffusion with A Source Term
作者团队：Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea Bertozzi, Stanley Osher, Bao Wang
论文标题：Graph Neural Networks with Learnable Structural and Positional Representations
作者团队：Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson
链接预测
论文标题：Revisiting Virtual Nodes in Graph Neural Networks for Link Prediction
作者团队：EunJeong Hwang, Veronika Thost, Shib Sankar Dasgupta, Tengfei Ma
论文标题： Counterfactual Graph Learning for Link Prediction
作者团队：Tong Zhao, Gang Liu, Daheng Wang, Wenhao Yu, Meng Jiang
论文标题： Benchmarking Graph Neural Networks on Dynamic Link Prediction
作者团队：Joakim Skarding, Matthew Hellmich, Bogdan Gabrys, Katarzyna Musial-Gabrys
论文标题：Few-shot graph link prediction with domain adaptation
作者团队：Hao Zhu, Mahashweta Das, Mangesh Bendre, Fei Wang, Hao Yang, Soha Hassoun
论文标题： Neural Link Prediction with Walk Pooling
作者团队：Liming Pan, Cheng Shi, Ivan Dokmanić
更深的GNN
论文标题：Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective
作者团队：Wei Huang, Yayong Li, weitao Du, Richard Xu, Jie Yin, Ling Chen, Miao Zhang
图数据增强
论文标题：Graph Condensation for Graph Neural Networks
作者团队：Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah
GNN的训练
论文标题：PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
作者团队： Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin
论文标题：IGLU: Efficient GCN Training via Lazy Updates
作者团队：S Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, SUNDARARAJAN SELLAMANICKAM
论文标题：Learning to Schedule Learning rate with Graph Neural Networks
作者团队：Yuanhao Xiong, Li-Cheng Lan, Xiangning Chen, Ruochen Wang, Cho-Jui Hsieh
论文标题：Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
作者团队：Anuroop Sriram, Abhishek Das, Brandon M Wood, C. Lawrence Zitnick
论文标题：EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression
作者团队：Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu
论文标题：Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
作者团队：Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut Kandemir, Anand Sivasubramaniam
论文标题：Large-Scale Representation Learning on Graphs via Bootstrapping
作者团队：Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L Dyer, Remi Munos, Petar Veličković, Michal Valko
图的自监督学习
论文标题：Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis
作者团队：Siyi Tang, Jared Dunnmon, Khaled Kamal Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel Rubin, Christopher Lee-Messer
论文标题：Pre-training Molecular Graph Representation with 3D Geometry
作者团队：Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang
论文标题：Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
作者团队： Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S Dhillon
论文标题：Automated Self-Supervised Learning for Graphs
作者团队： Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
GNN的可解释性
论文标题：Discovering Invariant Rationales for Graph Neural Networks
作者团队：Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua
论文标题：Explanations of Black-Box Models based on Directional Feature Interactions
作者团队：Aria Masoomi, Davin Hill, Zhonghui Xu, Craig P Hersh, Edwin K. Silverman, Peter J. Castaldi, Stratis Ioannidis, Jennifer Dy
论文标题：DEGREE: Decomposition Based Explanation for Graph Neural Networks
作者团队：Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu
论文标题：A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease
作者团队： Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L Goldman, William Ulrich, Daniel R Weinberger, Archana Venkataraman
论文标题：Explainable GNN-Based Models over Knowledge Graphs
作者团队：David Jaime Tena Cucala, Bernardo Cuenca Grau, Egor V. Kostylev, Boris Motik
论文标题：Efficient Neural Causal Discovery without Acyclicity Constraints
作者团队：Phillip Lippe, Taco Cohen, Efstratios Gavves
图分子生成
论文标题：Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design
作者团队：Wenhao Gao, Rocío Mercado, Connor W. Coley
论文标题：Data-Efficient Graph Grammar Learning for Molecular Generation
作者团队：Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
论文标题：GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation
作者团队： Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang
论文标题：Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction
作者团队：Mingyue Tang, Pan Li, Carl Yang
论文标题：GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification
作者团队： Joonhyung Park, Jaeyun Song, Eunho Yang
论文标题：Top-N: Equivariant Set and Graph Generation without Exchangeability
作者团队：Clement Vignac, Pascal Frossard
论文标题：Differentiable Scaffolding Tree for Molecule Optimization
作者团队：Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun
论文标题：Learning to Extend Molecular Scaffolds with Structural Motifs
作者团队：Krzysztof Maziarz, Henry Richard Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin Segler, Marc Brockschmidt
论文标题：Vitruvion: A Generative Model of Parametric CAD Sketches
作者团队：Ari Seff, Wenda Zhou, Nick Richardson, Ryan P Adams
图上的组合优化
论文标题：Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
作者团队：Benjamin Hudson, Qingbiao Li, Matthew Malencia, Amanda Prorok
论文标题：Neural Models for Output-Space Invariance in Combinatorial Problems
作者团队：Yatin Nandwani, Vidit Jain, Mausam ., Parag Singla
论文标题：What’s Wrong with Deep Learning in Tree Search for Combinatorial Optimization
作者团队：Maximilian Böther, Otto Kißig, Martin Taraz, Sarel Cohen, Karen Seidel, Tobias Friedrich
论文标题：Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs
作者团队：Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang
图物理研究
论文标题：Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks
作者团队： Marten Lienen, Stephan Günnemann
论文标题：R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning
作者团队：Shengyao Lu, Bang Liu, Keith G Mills, SHANGLING JUI, Di Niu
论文标题：Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions
作者团队：Nicholas Gao, Stephan Günnemann
论文标题：Message Passing Neural PDE Solvers
作者团队： Johannes Brandstetter, Daniel E. Worrall, Max Welling
论文标题：Constrained Graph Mechanics Networks
作者团队： Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang
论文标题：Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
作者团队： Anuroop Sriram, Abhishek Das, Brandon M Wood, C. Lawrence Zitnick
论文标题：Neural Relational Inference with Node-Specific Information
作者团队：Ershad Banijamali
论文标题：Predicting Physics in Mesh-reduced Space with Temporal Attention
作者团队：XU HAN, Han Gao, Tobias Pfaff, Jian-Xun Wang, Liping Liu
图上的生物和化学研究
论文标题：Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design
作者团队：Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola
论文标题：GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation
作者团队：Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang
论文标题：Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
作者团队：Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause
论文标题：Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
作者团队：Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Erica Teixeira Prates, Veronica G Melesse Vergara, Manesh B Shah, Austin Clyde, Thomas Brettin, Wibe Albert de Jong, Neeraj Kumar, Martha S Head, Rick L. Stevens, Peter Nugent, Daniel A Jacobson, James B Brown
论文标题：Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms
作者团队：Simin Hong, Anthony Cohn, David Crossland Hogg
论文标题：A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease
作者团队：Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L Goldman, William Ulrich, Daniel R Weinberger, Archana Venkataraman
论文标题：Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond
作者团队：Jonathan Godwin, Michael Schaarschmidt, Alexander L Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Veličković, James Kirkpatrick, Peter Battaglia
论文标题：Geometric Transformers for Protein Interface Contact Prediction
作者团队： Alex Morehead, Chen Chen, Jianlin Cheng
论文标题：OntoProtein: Protein Pretraining With Gene Ontology Embedding
作者团队： Ningyu Zhang, Zhen Bi, Xiaozhuan Liang, Siyuan Cheng, Haosen Hong, Shumin Deng, Qiang Zhang, Jiazhang Lian, Huajun Chen
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations
作者团队：Keir Adams, Lagnajit Pattanaik, Connor W. Coley
论文标题：Chemical-Reaction-Aware Molecule Representation Learning
作者团队：Hongwei Wang, Weijiang Li, Xiaomeng Jin, Kyunghyun Cho, Heng Ji, Jiawei Han, Martin Burke
论文标题：Spherical Message Passing for 3D Molecular Graphs
作者团队：Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji
时间序列GNN
论文标题：TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting
作者团队：Yuzhou Chen, Ignacio Segovia-Dominguez, Baris Coskunuzer, Yulia Gel
论文标题：Space-Time Graph Neural Networks
作者团队：Samar Hadou, Charilaos I Kanatsoulis, Alejandro Ribeiro
论文标题：Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks
作者团队：Andrea Cini, Ivan Marisca, Cesare Alippi
论文标题：Graph-Guided Network for Irregularly Sampled Multivariate Time Series
作者团队：Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik
论文标题：Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecasting
作者团队：Hyunwook Lee,Seungmin Jin,Hyeshin Chu,Hongkyu Lim,Sungahn
图上的多智能研究
论文标题：Context-Aware Sparse Deep Coordination Graphs
作者团队：Tonghan Wang, Liang Zeng, Weijun Dong, Qianlan Yang, Yang Yu, Chongjie Zhang
论文标题：Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory
作者团队：Zhi Zhang, Zhuoran Yang, Han Liu, Pratap Tokekar, Furong Huang
论文标题：Learning Graphon Mean Field Games and Approximate Nash Equilibria
作者团队：Kai Cui, Heinz Koeppl
论文标题：Graph-Enhanced Exploration for Goal-oriented Reinforcement Learning
作者团队：Jiarui Jin, Sijin Zhou, Weinan Zhang, Tong He, Yong Yu, Rasool Fakoor
论文标题：Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning
作者团队：Sunghoon Hong, Deunsol Yoon, Kee-Eung Kim
论文标题：C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks
作者团队：Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez
论文标题：Learning Object-Oriented Dynamics for Planning from Text
作者团队： Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart
图外推
Towards Distribution Shift of Node-Level Prediction on Graphs: An Invariance Perspective
作者团队：Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf
图上的关系建模
论文标题：Relational Multi-Task Learning: Modeling Relations between Data and Tasks
作者团队： Kaidi Cao, Jiaxuan You, Jure Leskovec
论文标题：Inductive Relation Prediction Using Analogy Subgraph Embeddings
作者团队： Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan
论文标题：Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space
作者团队：Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Senzhang Wang, Ming Lin, YuQi Zhang, Xiuyu Sun
论文标题：Graph-Relational Domain Adaptation
作者团队：Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang
论文标题：MoReL: Multi-omics Relational Learning Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian
论文标题：Know Your Action Set: Learning Action Relations for Reinforcement Learning
作者团队：Ayush Jain, Norio Kosaka, Kyung-Min Kim, Joseph J Lim
Graph Transformer
论文标题：Revisiting Over-smoothing in BERT from the Perspective of Graph
作者团队：Han Shi, JIAHUI GAO, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James Kwok
GNN和NLP结合
论文标题：GNN-LM: Language Modeling based on Global Contexts via GNN
作者团队：Yuxian Meng, Shi Zong, Xiaoya Li, Xiaofei Sun, Tianwei Zhang, Fei Wu, Jiwei Li
GNN偏微分方程
论文标题： Message Passing Neural PDE Solvers
作者团队：Johannes Brandstetter, Daniel E. Worrall, Max Welling
论文标题：Learning Time-dependent PDE Solver using Message Passing Graph Neural Networks
作者团队：Pourya Pilva, Ahmad Zareei
论文标题：Learning to Solve PDE-constrained Inverse Problems with Graph Networks
作者团队：Qingqing Zhao, David B. Lindell, Gordon Wetzstein
GNN的鲁棒性
论文标题：Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
作者团队：Yongqiang Chen, Han Yang, Yonggang Zhang, MA KAILI, Tongliang Liu, Bo Han, James Cheng
论文标题：Adversarial Robustness Through the Lens of Causality 、
作者团队：Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang
图上的随机块模型
论文标题：LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL
作者团队：Wei Lu
论文标题： DIGRAC: Digraph Clustering Based on Flow Imbalance
作者团队：Yixuan He, Gesine Reinert, Mihai Cucuringu
34. 图隐私计算和联邦学习
论文标题： Node-Level Differentially Private Graph Neural Networks
作者团队：Ameya Daigavane, Gagan Madan, Aditya Sinha, Abhradeep Guha Thakurta, Gaurav Aggarwal, Prateek Jain
论文标题： Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
作者团队：Or Litany, Haggai Maron, David Acuna, Jan Kautz, Gal Chechik, Sanja Fidler
论文标题：Federated Inference through Aligning Local Representations and Learning a Consensus Graph
作者团队：Tengfei Ma, Trong Nghia Hoang, Jie Chen
图神经网络架构搜索
论文标题： AutoCoG: A Unified Data-Modal Co-Search Framework for Graph Neural Networks
作者团队：Duc N.M Hoang, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang
论文标题： A Transferable General-Purpose Predictor for Neural Architecture Search
作者团队：Fred X. Han, Fabian Chudak, Keith G Mills, Mohammad Salameh, Parsa Riahi, Jialin Zhang, Wei Lu, SHANGLING JUI, Di Niu
其它
论文标题：Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels
作者团队：Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin CUI
论文标题：End-to-End Learning of Probabilistic Hierarchies on Graphs
作者团队： Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann
论文标题：Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
作者团队：Wenqing Zheng, Edward W Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian
论文标题：Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph
作者团队：Dacheng Yin, Xuanchi Ren, Chong Luo, Yuwang Wang, Zhiwei Xiong, Wenjun Zeng
论文标题：GLASS: GNN with Labeling Tricks for Subgraph Representation Learning
作者团队：Xiyuan Wang, Muhan Zhang
论文标题：NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs
作者团队：Mikhail Galkin, Etienne Denis, Jiapeng Wu, William L. Hamilton
论文标题：Query Embedding on Hyper-Relational Knowledge Graphs
作者团队：Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin
Reference
1.ICLR 2022图学习领域都在研究什么？Open Review投稿文章一览 - 知乎
2. GitHub - naganandy/graph-based-deep-learning-literature: links to conference publications in graph-based deep learning