| Convolutional neural networks on graphs with fast localized spectral filtering M Defferrard, X Bresson, P Vandergheynst Advances in neural information processing systems 29, 2016 | 11648 | 2016 |
| Benchmarking graph neural networks VP Dwivedi, CK Joshi, T Laurent, Y Bengio, X Bresson Journal of Machine Learning Research (JMLR), 2020 | 1629 | 2020 |
| A generalization of transformer networks to graphs VP Dwivedi, X Bresson arXiv preprint arXiv:2012.09699, 2020 | 1370 | 2020 |
| Structured sequence modeling with graph convolutional recurrent networks Y Seo, M Defferrard, P Vandergheynst, X Bresson International conference on neural information processing, 362-373, 2018 | 1287 | 2018 |
| Fast global minimization of the active contour/snake model X Bresson, S Esedoḡlu, P Vandergheynst, JP Thiran, S Osher Journal of Mathematical Imaging and vision 28 (2), 151-167, 2007 | 1223 | 2007 |
| Cayleynets: Graph convolutional neural networks with complex rational spectral filters R Levie, F Monti, X Bresson, MM Bronstein IEEE Transactions on Signal Processing 67 (1), 97-109, 2018 | 970 | 2018 |
| Bregmanized nonlocal regularization for deconvolution and sparse reconstruction X Zhang, M Burger, X Bresson, S Osher SIAM journal on imaging sciences 3 (3), 253-276, 2010 | 823 | 2010 |
| Fma: A dataset for music analysis M Defferrard, K Benzi, P Vandergheynst, X Bresson arXiv preprint arXiv:1612.01840, 2016 | 752 | 2016 |
| Geometric matrix completion with recurrent multi-graph neural networks F Monti, M Bronstein, X Bresson Advances in neural information processing systems 30, 2017 | 744 | 2017 |
| Residual gated graph convnets X Bresson, T Laurent arXiv preprint arXiv:1711.07553, 2017 | 703 | 2017 |
| An efficient graph convolutional network technique for the travelling salesman problem CK Joshi, T Laurent, X Bresson arXiv preprint arXiv:1906.01227, 2019 | 635 | 2019 |
| Geometric applications of the split Bregman method: segmentation and surface reconstruction T Goldstein, X Bresson, S Osher Journal of scientific computing 45 (1), 272-293, 2010 | 609 | 2010 |
| Graph neural networks with learnable structural and positional representations VP Dwivedi, AT Luu, T Laurent, Y Bengio, X Bresson International Conference on Learning Representations (ICLR) 2022, 2021 | 583 | 2021 |
| Fast dual minimization of the vectorial total variation norm and applications to color image processing X Bresson, TF Chan Inverse problems and imaging 2 (4), 455-484, 2008 | 498 | 2008 |
| G-retriever: Retrieval-augmented generation for textual graph understanding and question answering X He, Y Tian, Y Sun, NV Chawla, T Laurent, Y LeCun, X Bresson, B Hooi Neural Information Processing Systems (NeurIPS) 2024, 2024 | 405 | 2024 |
| Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning X He, X Bresson, T Laurent, A Perold, Y LeCun, B Hooi International Conference on Learning Representations (ICLR) 2024, 2023 | 340* | 2023 |
| Local histogram based segmentation using the Wasserstein distance K Ni, X Bresson, T Chan, S Esedoglu International journal of computer vision 84 (1), 97-111, 2009 | 329 | 2009 |
| Matrix completion on graphs V Kalofolias, X Bresson, M Bronstein, P Vandergheynst arXiv preprint arXiv:1408.1717, 2014 | 272 | 2014 |
| Completely convex formulation of the Chan-Vese image segmentation model ES Brown, TF Chan, X Bresson International journal of computer vision 98 (1), 103-121, 2012 | 236 | 2012 |
| A variational model for object segmentation using boundary information and shape prior driven by the Mumford-Shah functional X Bresson, P Vandergheynst, JP Thiran International Journal of Computer Vision 68 (2), 145-162, 2006 | 225 | 2006 |
Pierre VandergheynstProfessor of Electrical Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL)Verified email at epfl.ch
