| Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention A Katharopoulos, A Vyas, N Pappas, F Fleuret International Conference on Machine Learning (ICML), 2020 | 688 | 2020 |
| Not all samples are created equal: Deep learning with importance sampling A Katharopoulos, F Fleuret International Conference on Machine Learning (ICML), 2018 | 361 | 2018 |
| Fast transformers with clustered attention A Vyas, A Katharopoulos, F Fleuret Neural Information Processing Systems (NeurIPS), 2020 | 92 | 2020 |
| Biased importance sampling for deep neural network training A Katharopoulos, F Fleuret arXiv preprint arXiv:1706.00043, 2017 | 65 | 2017 |
| Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks D Paschalidou, A Katharopoulos, A Geiger, S Fidler Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2021, 2021 | 60 | 2021 |
| Processing megapixel images with deep attention-sampling models A Katharopoulos, F Fleuret International Conference on Machine Learning (ICML), 2019 | 53 | 2019 |
| Fast supervised lda for discovering micro-events in large-scale video datasets A Katharopoulos, D Paschalidou, C Diou, A Delopoulos Proceedings of the 24th ACM international conference on Multimedia, 332-336, 2016 | 6 | 2016 |
| Learning local feature aggregation functions with backpropagation A Katharopoulos, D Paschalidou, C Diou, A Delopoulos 2017 25th European Signal Processing Conference (EUSIPCO), 748-752, 2017 | 1 | 2017 |
| Self Supervision Does Not Help Natural Language Supervision at Scale F Weers, V Shankar, A Katharopoulos, Y Yang, T Gunter arXiv preprint arXiv:2301.07836, 2023 | | 2023 |
| Masked Autoencoding Does Not Help Natural Language Supervision at Scale F Weers, V Shankar, A Katharopoulos, Y Yang, T Gunter Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | | 2023 |
| Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models A Katharopoulos EPFL, 2022 | | 2022 |
| Formal Name (English) L'IDIAP Laboratory C Atanasoaei, SO Ba, S Bengio, JI Biel Tres, R Boghetti, H Bourlard, ... | | |
| Supplementary Material for Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks. D Paschalidou, A Katharopoulos, A Geiger, S Fidler | | |
| Not All Samples Are Created Equal Supplementary material A Katharopoulos, F Fleuret | | |
François FleuretUniversity of GenevaVerified email at fleuret.org
