Title |
|---|
 Adversarial Graph DisentanglementIEEE Transactions on Artificial Intelligence (IEEE TAI), 2021 |
 Size-Invariant Graph Representations for Graph Classification
ExtrapolationsInternational Conference on Machine Learning (ICML), 2021 |
 Weisfeiler and Lehman Go Topological: Message Passing Simplicial
NetworksInternational Conference on Machine Learning (ICML), 2021 |
 Autobahn: Automorphism-based Graph Neural NetsNeural Information Processing Systems (NeurIPS), 2021 |
 Efficient and Interpretable Robot Manipulation with Graph Neural
NetworksIEEE Robotics and Automation Letters (RA-L), 2021 |
 Task-Agnostic Morphology EvolutionInternational Conference on Learning Representations (ICLR), 2021 |
 |
 Accurate Learning of Graph Representations with Graph Multiset PoolingInternational Conference on Learning Representations (ICLR), 2021 |
 Combinatorial optimization and reasoning with graph neural networksInternational Joint Conference on Artificial Intelligence (IJCAI), 2021 |
 Topological Graph Neural NetworksInternational Conference on Learning Representations (ICLR), 2021 |
 Identity-aware Graph Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2021 |
 Learning Parametrised Graph Shift OperatorsInternational Conference on Learning Representations (ICLR), 2021 |
 A Generalized Weisfeiler-Lehman Graph KernelMachine-mediated learning (ML), 2021 |
 SPAGAN: Shortest Path Graph Attention NetworkInternational Joint Conference on Artificial Intelligence (IJCAI), 2019 |
 Graph Neural Networks: Taxonomy, Advances and TrendsACM Transactions on Intelligent Systems and Technology (ACM TIST), 2020 |
 Rethinking the Promotion Brought by Contrastive Learning to
Semi-Supervised Node ClassificationInternational Joint Conference on Artificial Intelligence (IJCAI), 2020 |
 |
 Design Space for Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2020 |
 Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node
Representation LearningNeural Information Processing Systems (NeurIPS), 2020 |
 On Graph Neural Networks versus Graph-Augmented MLPsInternational Conference on Learning Representations (ICLR), 2020 |
 Co-embedding of Nodes and Edges with Graph Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 |
 A Simple Spectral Failure Mode for Graph Convolutional NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 |
 Incorporating Symbolic Domain Knowledge into Graph Neural NetworksMachine-mediated learning (ML), 2020 |
 From Local Structures to Size Generalization in Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2020 |
 Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text
GenerationConference on Empirical Methods in Natural Language Processing (EMNLP), 2020 |
 Unsupervised Joint -node Graph Representations with Compositional
Energy-Based ModelsNeural Information Processing Systems (NeurIPS), 2020 |
 On the Universality of Rotation Equivariant Point Cloud NetworksInternational Conference on Learning Representations (ICLR), 2020 |
