| Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms H Xiao, K Rasul, R Vollgraf arXiv preprint arXiv:1708.07747, 2017 | 4242 | 2017 |
| Contextual string embeddings for sequence labeling A Akbik, D Blythe, R Vollgraf Proceedings of the 27th international conference on computational …, 2018 | 1156 | 2018 |
| FLAIR: An easy-to-use framework for state-of-the-art NLP A Akbik, T Bergmann, D Blythe, K Rasul, S Schweter, R Vollgraf Proceedings of the 2019 conference of the North American chapter of the …, 2019 | 461 | 2019 |
| Pooled contextualized embeddings for named entity recognition A Akbik, T Bergmann, R Vollgraf Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 246 | 2019 |
| Texture synthesis with spatial generative adversarial networks N Jetchev, U Bergmann, R Vollgraf arXiv preprint arXiv:1611.08207, 2016 | 153 | 2016 |
| Quadratic optimization for simultaneous matrix diagonalization R Vollgraf, K Obermayer IEEE Transactions on Signal Processing 54 (9), 3270-3278, 2006 | 135 | 2006 |
| Fashion-mnist: A novel image dataset for benchmarking machine learning algorithms. arXiv 2017 H Xiao, K Rasul, R Vollgraf arXiv preprint arXiv:1708.07747, 2017 | 131 | 2017 |
| Learning texture manifolds with the periodic spatial GAN U Bergmann, N Jetchev, R Vollgraf arXiv preprint arXiv:1705.06566, 2017 | 117 | 2017 |
| From grids to places M Franzius, R Vollgraf, L Wiskott Journal of computational neuroscience 22 (3), 297-299, 2007 | 80 | 2007 |
| Multivariate probabilistic time series forecasting via conditioned normalizing flows K Rasul, AS Sheikh, I Schuster, U Bergmann, R Vollgraf arXiv preprint arXiv:2002.06103, 2020 | 55 | 2020 |
| Fashion DNA: merging content and sales data for recommendation and article mapping C Bracher, S Heinz, R Vollgraf arXiv preprint arXiv:1609.02489, 2016 | 42 | 2016 |
| Generating high-resolution fashion model images wearing custom outfits G Yildirim, N Jetchev, R Vollgraf, U Bergmann Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 35 | 2019 |
| Improved optimal linear filters for the discrimination of multichannel waveform templates for spike-sorting applications R Vollgraf, K Obermayer IEEE Signal Processing Letters 13 (3), 121-124, 2006 | 30 | 2006 |
| Multi dimensional ICA to separate correlated sources R Vollgraf, K Obermayer Advances in neural information processing systems 14, 2001 | 25 | 2001 |
| A deep learning system for predicting size and fit in fashion e-commerce AS Sheikh, R Guigourès, E Koriagin, YK Ho, R Shirvany, R Vollgraf, ... Proceedings of the 13th ACM conference on recommender systems, 110-118, 2019 | 23 | 2019 |
| Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting K Rasul, C Seward, I Schuster, R Vollgraf International Conference on Machine Learning, 8857-8868, 2021 | 19 | 2021 |
| Task-aware representation of sentences for generic text classification K Halder, A Akbik, J Krapac, R Vollgraf Proceedings of the 28th International Conference on Computational …, 2020 | 18 | 2020 |
| An LSTM-based dynamic customer model for fashion recommendation S Heinz, C Bracher, R Vollgraf arXiv preprint arXiv:1708.07347, 2017 | 18 | 2017 |
| Meta-learning for size and fit recommendation in fashion J Lasserre, AS Sheikh, E Koriagin, U Bergman, R Vollgraf, R Shirvany Proceedings of the 2020 SIAM international conference on data mining, 55-63, 2020 | 13 | 2020 |
| Optimal filtering for spike sorting of multi-site electrode recordings R Vollgraf, M Munk, K Obermayer Network: Computation in Neural Systems 16 (1), 85-113, 2005 | 13 | 2005 |
Kashif RasulZalando ResearchVerified email at zalando.de
