| Universal invariant and equivariant graph neural networks N Keriven, G Peyré Advances in Neural Information Processing Systems 32, 2019 | 333 | 2019 |
| Not too little, not too much: a theoretical analysis of graph (over) smoothing N Keriven Advances in Neural Information Processing Systems (NeurIPS), 2022 | 115 | 2022 |
| Convergence and Stability of Graph Convolutional Networks on Large Random Graphs N Keriven, A Bietti, S Vaiter Advances in Neural Information Processing Systems 33, 21512--21523, 2020 | 104 | 2020 |
| Sketching for large-scale learning of mixture models N Keriven, A Bourrier, R Gribonval, P Pérez Information and Inference: A Journal of the IMA 7 (3), 447-508, 2018 | 100 | 2018 |
| Compressive statistical learning with random feature moments R Gribonval, G Blanchard, N Keriven, Y Traonmilin Mathematical Statistics and Learning 3 (2), 113-164, 2021 | 74 | 2021 |
| Compressive K-means N Keriven, N Tremblay, Y Traonmilin, R Gribonval 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 72 | 2017 |
| NEWMA: a new method for scalable model-free online change-point detection N Keriven, D Garreau, I Poli IEEE Transactions on Signal Processing 68, 3515-3528, 2020 | 55 | 2020 |
| The geometry of off-the-grid compressed sensing C Poon, N Keriven, G Peyré Foundations of Computational Mathematics 23 (1), 241-327, 2023 | 37* | 2023 |
| On the Universality of Graph Neural Networks on Large Random Graphs N Keriven, A Bietti, S Vaiter Advances in Neural Information Processing Systems 34, 2021 | 35 | 2021 |
| Support localization and the fisher metric for off-the-grid sparse regularization C Poon, N Keriven, G Peyré The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 26 | 2019 |
| Non-negative group sparsity with subspace note modelling for polyphonic transcription K O’Hanlon, H Nagano, N Keriven, MD Plumbley IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (3), 530-542, 2016 | 25 | 2016 |
| Sketching data sets for large-scale learning: Keeping only what you need R Gribonval, A Chatalic, N Keriven, V Schellekens, L Jacques, P Schniter IEEE Signal Processing Magazine 38 (5), 12-36, 2021 | 24 | 2021 |
| Large-scale high-dimensional clustering with fast sketching A Chatalic, R Gribonval, N Keriven 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 23 | 2018 |
| Statistical learning guarantees for compressive clustering and compressive mixture modeling R Gribonval, G Blanchard, N Keriven, Y Traonmilin arXiv preprint arXiv:2004.08085, 2020 | 21 | 2020 |
| What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding N Keriven, S Vaiter Advances in Neural Information Processing Systems 36, 11823-11849, 2023 | 16 | 2023 |
| Sparse and smooth: improved guarantees for spectral clustering in the dynamic stochastic block model N Keriven, S Vaiter Electronic Journal of Statistics 16 (1), 1330 - 1366, 2022 | 16 | 2022 |
| Blind source separation using mixtures of alpha-stable distributions N Keriven, A Deleforge, A Liutkus 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 14 | 2018 |
| Sketching datasets for large-scale learning (long version) R Gribonval, A Chatalic, N Keriven, V Schellekens, L Jacques, P Schniter arXiv preprint arXiv:2008.01839, 2020 | 12 | 2020 |
| Instance optimal decoding and the restricted isometry property N Keriven, R Gribonval Journal of Physics: Conference Series 1131 (1), 012002, 2018 | 11 | 2018 |
| Structured sparsity using backwards elimination for automatic music transcription N Keriven, K O'Hanlon, MD Plumbley 2013 IEEE International Workshop on Machine Learning for Signal Processing …, 2013 | 8 | 2013 |
Rémi GribonvalInria & ENS de LyonVerified email at ens-lyon.fr
