| Semi-supervised classification with graph convolutional networks TN Kipf, M Welling 5th International Conference on Learning Representations (ICLR-17), 2016 | 6445 | 2016 |
| Modeling Relational Data with Graph Convolutional Networks M Schlichtkrull*, TN Kipf*, P Bloem, R Berg, I Titov, M Welling 15th European Semantic Web Conference (ESWC-18), 2017 | 960 | 2017 |
| Variational Graph Auto-Encoders TN Kipf, M Welling NeurIPS Workshop on Bayesian Deep Learning (NeurIPS-16 BDL), 2016 | 743 | 2016 |
| Graph convolutional matrix completion R Berg, TN Kipf, M Welling KDD Deep Learning Day (KDD-18 DLD), 2017 | 290 | 2017 |
| MolGAN: An implicit generative model for small molecular graphs N De Cao, T Kipf ICML Workshop on Theoretical Foundations and Applications of Deep …, 2018 | 249 | 2018 |
| Neural Relational Inference for Interacting Systems T Kipf*, E Fetaya*, KC Wang, M Welling, R Zemel 35th International Conference on Machine Learning (ICML-18), 2018 | 244 | 2018 |
| Hyperspherical Variational Auto-Encoders TR Davidson*, L Falorsi*, N De Cao*, T Kipf, JM Tomczak 34th Conference on Uncertainty in Artificial Intelligence (UAI-18), 2018 | 140 | 2018 |
| Learned cardinalities: Estimating correlated joins with deep learning A Kipf, T Kipf, B Radke, V Leis, P Boncz, A Kemper Conference on Innovative Data Systems Research (CIDR-19), 2018 | 102 | 2018 |
| Towards Sparse Hierarchical Graph Classifiers C Cangea*, P Veličković*, N Jovanović, T Kipf, P Liò arXiv preprint arXiv:1811.01287, 2018 | 65 | 2018 |
| Semi-supervised classification with graph convolutional networks. arXiv 2016 TN Kipf, M Welling arXiv preprint arXiv:1609.02907, 0 | 58 | |
| Contrastive learning of structured world models T Kipf, E van der Pol, M Welling arXiv preprint arXiv:1911.12247, 2019 | 43 | 2019 |
| Superradiance and collective gain in multimode optomechanics T Kipf, GS Agarwal Physical Review A 90 (5), 053808, 2014 | 29 | 2014 |
| Object-Centric Learning with Slot Attention F Locatello*, D Weissenborn, T Unterthiner, A Mahendran, G Heigold, ... arXiv preprint arXiv:2006.15055, 2020 | 15 | 2020 |
| CompILE: Compositional imitation learning and execution T Kipf, Y Li, H Dai, V Zambaldi, A Sanchez-Gonzalez, E Grefenstette, ... International Conference on Machine Learning, 3418-3428, 2019 | 15 | 2019 |
| Semi-Supervised Classification with Graph Convolutional Networks. CoRR abs/1609.02907 (2016) NK Thomas, M Welling arXiv preprint arXiv:1609.02907, 2016 | 15 | 2016 |
| Extraction of airways using graph neural networks R Selvan, T Kipf, M Welling, JH Pedersen, J Petersen, M de Bruijne arXiv preprint arXiv:1804.04436, 2018 | 14* | 2018 |
| Estimating cardinalities with deep sketches A Kipf, D Vorona, J Müller, T Kipf, B Radke, V Leis, P Boncz, T Neumann, ... Proceedings of the 2019 International Conference on Management of Data, 1937 …, 2019 | 10 | 2019 |
| Compositional imitation learning: Explaining and executing one task at a time T Kipf, Y Li, H Dai, V Zambaldi, E Grefenstette, P Kohli, P Battaglia arXiv preprint arXiv:1812.01483, 2018 | 10 | 2018 |
| Graph Convolutional Networks T Kipf https://tkipf.github.io/graph-convolutional-networks/, 2016 | 7 | 2016 |
| Plannable Approximations to MDP Homomorphisms: Equivariance under Actions E van der Pol, T Kipf, FA Oliehoek, M Welling arXiv preprint arXiv:2002.11963, 2020 | 5 | 2020 |
Max WellingProfessor Machine Learning, University of AmsterdamVerified email at uva.nl
