| Auto-encoding variational bayes DP Kingma, M Welling International Conference on Learning Representations (ICLR), 2013 | 38510 | 2013 |
| Semi-supervised classification with graph convolutional networks TN Kipf, M Welling International Conference on Learning Representations (ICLR), 2016 | 38006 | 2016 |
| Modeling relational data with graph convolutional networks M Schlichtkrull, TN Kipf, P Bloem, R Van Den Berg, I Titov, M Welling The semantic web: 15th international conference, ESWC 2018, Heraklion, Crete …, 2018 | 5585 | 2018 |
| Semi-supervised learning with deep generative models DP Kingma, S Mohamed, D Jimenez Rezende, M Welling Advances in neural information processing systems 27, 2014 | 3622 | 2014 |
| Variational graph auto-encoders TN Kipf, M Welling NeurIPS Workshop on Bayesian Deep Learning (NeurIPS BDL), 2016 | 3113 | 2016 |
| Bayesian learning via stochastic gradient Langevin dynamics M Welling, YW Teh Proceedings of the 28th international conference on machine learning (ICML …, 2011 | 2985 | 2011 |
| An introduction to variational autoencoders DP Kingma, M Welling Foundations and Trends® in Machine Learning 12 (4), 307-392, 2019 | 2895 | 2019 |
| Group equivariant convolutional networks T Cohen, M Welling International conference on machine learning, 2990-2999, 2016 | 2203 | 2016 |
| Improved variational inference with inverse autoregressive flow DP Kingma, T Salimans, R Jozefowicz, X Chen, I Sutskever, M Welling Advances in neural information processing systems 29, 2016 | 2126 | 2016 |
| Attention-based deep multiple instance learning M Ilse, J Tomczak, M Welling International conference on machine learning, 2127-2136, 2018 | 1892 | 2018 |
| Variational dropout and the local reparameterization trick DP Kingma, T Salimans, M Welling Advances in neural information processing systems 28, 2015 | 1763 | 2015 |
| Attention, learn to solve routing problems! W Kool, H Van Hoof, M Welling International Conference on Learning Representations (ICLR), 2018 | 1533 | 2018 |
| Learning sparse neural networks through regularization C Louizos, M Welling, DP Kingma International Conference on Learning Representations (ICLR), 2017 | 1255 | 2017 |
| Spherical cnns TS Cohen, M Geiger, J Köhler, M Welling International Conference on Learning Representations (ICLR), 2018 | 1107 | 2018 |
| Neural relational inference for interacting systems T Kipf, E Fetaya, KC Wang, M Welling, R Zemel International conference on machine learning, 2688-2697, 2018 | 990 | 2018 |
| Unsupervised learning of models for recognition M Weber, M Welling, P Perona Computer Vision-ECCV 2000: 6th European Conference on Computer Vision Dublin …, 2000 | 975 | 2000 |
| Graph convolutional matrix completion R Van Den Berg, NK Thomas, M Welling KDD Deep Learning Day (KDD DLD), 2017 | 915 | 2017 |
| Visualizing deep neural network decisions: Prediction difference analysis LM Zintgraf, TS Cohen, T Adel, M Welling The fifth International Conference on Learning Representations (ICLR), 2017 | 861 | 2017 |
| E (n) equivariant graph neural networks VG Satorras, E Hoogeboom, M Welling International conference on machine learning, 9323-9332, 2021 | 843 | 2021 |
| Causal effect inference with deep latent-variable models C Louizos, U Shalit, JM Mooij, D Sontag, R Zemel, M Welling Advances in neural information processing systems 30, 2017 | 837 | 2017 |
Paul NewmanProfessor University of OxfordVerified email at robots.ox.ac.uk
