| SLIC superpixels compared to state-of-the-art superpixel methods R Achanta, A Shaji, K Smith, A Lucchi, P Fua, S Süsstrunk IEEE transactions on pattern analysis and machine intelligence 34 (11), 2274 …, 2012 | 7387 | 2012 |
| Slic superpixels R Achanta, A Shaji, K Smith, A Lucchi, P Fua, S Süsstrunk | 1375* | 2010 |
| Stabilizing training of generative adversarial networks through regularization K Roth, A Lucchi, S Nowozin, T Hofmann arXiv preprint arXiv:1705.09367, 2017 | 294 | 2017 |
| Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks With Learned Shape Features. A Lucchi, K Smith, R Achanta, G Knott, P Fua IEEE transactions on medical imaging, 2011 | 263 | 2011 |
| Learning aerial image segmentation from online maps P Kaiser, JD Wegner, A Lucchi, M Jaggi, T Hofmann, K Schindler IEEE Transactions on Geoscience and Remote Sensing 55 (11), 6054-6068, 2017 | 179 | 2017 |
| Probabilistic bag-of-hyperlinks model for entity linking OE Ganea, M Ganea, A Lucchi, C Eickhoff, T Hofmann Proceedings of the 25th International Conference on World Wide Web, 927-938, 2016 | 129 | 2016 |
| A fully automated approach to segmentation of irregularly shaped cellular structures in EM images A Lucchi, K Smith, R Achanta, V Lepetit, P Fua Medical Image Computing and Computer-Assisted Intervention–MICCAI 2010, 463-471, 2010 | 127 | 2010 |
| Swisscheese at semeval-2016 task 4: Sentiment classification using an ensemble of convolutional neural networks with distant supervision J Deriu, M Gonzenbach, F Uzdilli, A Lucchi, VD Luca, M Jaggi Proceedings of the 10th international workshop on semantic evaluation, 1124-1128, 2016 | 118 | 2016 |
| Leveraging large amounts of weakly supervised data for multi-language sentiment classification J Deriu, A Lucchi, V De Luca, A Severyn, S Müller, M Cieliebak, ... Proceedings of the 26th international conference on world wide web, 1045-1052, 2017 | 111 | 2017 |
| Radio frequency interference mitigation using deep convolutional neural networks J Akeret, C Chang, A Lucchi, A Refregier Astronomy and computing 18, 35-39, 2017 | 106 | 2017 |
| Variance reduced stochastic gradient descent with neighbors T Hofmann, A Lucchi, S Lacoste-Julien, B McWilliams arXiv preprint arXiv:1506.03662, 2015 | 103 | 2015 |
| Sub-sampled cubic regularization for non-convex optimization JM Kohler, A Lucchi International Conference on Machine Learning, 1895-1904, 2017 | 97 | 2017 |
| Structured image segmentation using kernelized features A Lucchi, Y Li, K Smith, P Fua European conference on computer vision, 400-413, 2012 | 78 | 2012 |
| Exponential convergence rates for Batch Normalization: The power of length-direction decoupling in non-convex optimization J Kohler, H Daneshmand, A Lucchi, M Zhou, K Neymeyr, T Hofmann AISTATS 2018, 2018 | 76* | 2018 |
| Escaping saddles with stochastic gradients H Daneshmand, J Kohler, A Lucchi, T Hofmann International Conference on Machine Learning (ICML), 2018 | 76 | 2018 |
| Are Spatial and Global Constraints Really Necessary for Segmentation? A Lucchi, Y Li, X Boix, K Smith, P Fua, ETH BIWI IEEE International Conference on Computer Vision (ICCV), 2011 | 75 | 2011 |
| Quantum generative adversarial networks for learning and loading random distributions C Zoufal, A Lucchi, S Woerner npj Quantum Information 5 (1), 1-9, 2019 | 68 | 2019 |
| Local saddle point optimization: A curvature exploitation approach L Adolphs, H Daneshmand, A Lucchi, T Hofmann AISTATS 2018, 2018 | 68 | 2018 |
| Learning for structured prediction using approximate subgradient descent with working sets A Lucchi, Y Li, P Fua Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 67 | 2013 |
| An online learning approach to generative adversarial networks P Grnarova, KY Levy, A Lucchi, T Hofmann, A Krause International Conference on Learning Representations (ICLR), 2017 | 63 | 2017 |
Pascal FuaProfessor Computer Science, EPFLVerified email at epfl.ch
