| 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 | 10998 | 2012 |
| Slic superpixels R Achanta, A Shaji, K Smith, A Lucchi, P Fua, S Süsstrunk | 1784* | 2010 |
| The power of quantum neural networks A Abbas, D Sutter, C Zoufal, A Lucchi, A Figalli, S Woerner Nature Computational Science 1 (6), 403-409, 2021 | 886 | 2021 |
| Stabilizing training of generative adversarial networks through regularization K Roth, A Lucchi, S Nowozin, T Hofmann Advances in neural information processing systems 30, 2017 | 541 | 2017 |
| Quantum generative adversarial networks for learning and loading random distributions C Zoufal, A Lucchi, S Woerner npj Quantum Information 5 (1), 103, 2019 | 396 | 2019 |
| 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 | 351 | 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 | 351 | 2011 |
| Radio frequency interference mitigation using deep convolutional neural networks J Akeret, C Chang, A Lucchi, A Refregier Astronomy and computing 18, 35-39, 2017 | 233 | 2017 |
| Sub-sampled cubic regularization for non-convex optimization JM Kohler, A Lucchi International Conference on Machine Learning, 1895-1904, 2017 | 212 | 2017 |
| Neural symbolic regression that scales L Biggio, T Bendinelli, A Neitz, A Lucchi, G Parascandolo International Conference on Machine Learning, 936-945, 2021 | 201 | 2021 |
| Topological map extraction from overhead images Z Li, JD Wegner, A Lucchi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 189 | 2019 |
| Escaping saddles with stochastic gradients H Daneshmand, J Kohler, A Lucchi, T Hofmann International Conference on Machine Learning (ICML), 2018 | 180 | 2018 |
| Variance reduced stochastic gradient descent with neighbors T Hofmann, A Lucchi, S Lacoste-Julien, B McWilliams Advances in Neural Information Processing Systems 28, 2015 | 180 | 2015 |
| 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 | 170 | 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 | 166 | 2016 |
| Swisscheese at semeval-2016 task 4: Sentiment classification using an ensemble of convolutional neural networks with distant supervision JM Deriu, M Gonzenbach, F Uzdilli, A Lucchi, V De Luca, M Jaggi Proceedings of the 10th international workshop on semantic evaluation …, 2016 | 165 | 2016 |
| 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 | 159* | 2018 |
| Fast cosmic web simulations with generative adversarial networks AC Rodriguez, T Kacprzak, A Lucchi, A Amara, R Sgier, J Fluri, ... Computational Astrophysics and Cosmology 5 (1), 1-11, 2018 | 158 | 2018 |
| Cosmological constraints with deep learning from KiDS-450 weak lensing maps J Fluri, T Kacprzak, A Lucchi, A Refregier, A Amara, T Hofmann, ... Physical Review D 100 (6), 063514, 2019 | 151 | 2019 |
| Local saddle point optimization: A curvature exploitation approach L Adolphs, H Daneshmand, A Lucchi, T Hofmann AISTATS 2018, 2018 | 138 | 2018 |
Thomas HofmannProfessor of Computer Science, ETH Zurichยืนยันอีเมลแล้วที่ inf.ethz.ch