| Texture synthesis with spatial generative adversarial networks N Jetchev, U Bergmann, R Vollgraf NIPS 2016 adversarial learning workshop, Barcelona, Spain, 2016 | 218 | 2016 |
| The conditional analogy gan: Swapping fashion articles on people images N Jetchev, U Bergmann International Conference on Computer Vision 2017 - Computer Vision for …, 2017 | 180 | 2017 |
| Learning texture manifolds with the periodic spatial GAN U Bergmann, N Jetchev, R Vollgraf International Conference for Machine Learning (ICML) 2017, 2017 | 171 | 2017 |
| Multi-variate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows K Rasul, AS Sheikh, I Schuster, U Bergmann, R Vollgraf International Conference on Learning Representations (ICLR 2021), 2021 | 161 | 2021 |
| Scene representation transformer: Geometry-free novel view synthesis through set-latent scene representations MSM Sajjadi, H Meyer, E Pot, U Bergmann, K Greff, N Radwan, S Vora, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 125 | 2022 |
| A Deep Learning System for Predicting Size and Fit in Fashion E-Commerce AS Sheikh, R Guigoures, E Koriagin, YK Ho, R Shirvany, R Vollgraf, ... Thirteenth ACM Conference on Recommender Systems (RecSys '19), September 16 …, 2019 | 57 | 2019 |
| Generating High-Resolution Fashion Model Images Wearing Custom Outfits G Yildirim, N Jetchev, R Vollgraf, U Bergmann International Conference on Computer Vision, ICCV 2019, Workshop on Computer …, 2019 | 50 | 2019 |
| A hierarchical bayesian model for size recommendation in fashion R Guigourès, YK Ho, E Koriagin, AS Sheikh, U Bergmann, R Shirvany Proceedings of the 12th ACM conference on recommender systems, 392-396, 2018 | 42 | 2018 |
| Disentangling Multiple Conditional Inputs in GANs G Yildirim, C Seward, U Bergmann In Proceedings of KDD Fashion Workshop (KDD), 2018 | 32 | 2018 |
| Meta-Learning for Size and Fit Recommendation in Fashion J Lasserre, AS Sheikh, E Koriagin, U Bergmann, R Vollgraf, R Shirvany Proceedings of the 2020 SIAM International Conference on Data Mining, 55-63, 2020 | 27 | 2020 |
| Self-organization of topographic bilinear networks for invariant recognition U Bergmann, C von der Malsburg Neural Computation 23 (11), 2770-2797, 2011 | 17 | 2011 |
| Stochastic Maximum Likelihood Optimization via Hypernetworks AS Sheikh, K Rasul, A Merentitis, U Bergmann 31st Conference on Neural Information Processing Systems (NIPS 2017), Long …, 2017 | 13 | 2017 |
| GANosaic: Mosaic Creation with Generative Texture Manifolds N Jetchev, U Bergmann, C Seward 31st Conference on Neural Information Processing Systems (NIPS 2017), Long …, 2017 | 9 | 2017 |
| Self-organization of steerable topographic mappings as basis for translation invariance J Zhu, U Bergmann, C Von Der Malsburg International Conference on Artificial Neural Networks, 414-419, 2010 | 7 | 2010 |
| Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation MWH Remme*, U Bergmann*, D Alevi, S Schreiber, H Sprekeler, ... PLOS Computational Biology 17 (12), e1009681, 2021 | 6 | 2021 |
| First Order Generative Adversarial Networks C Seward, T Unterthiner, U Bergmann, N Jetchev, S Hochreiter 35th International Conference on Machine Learning (ICML), 2018 | 6 | 2018 |
| Transform the Set: Memory Attentive Generation of Guided and Unguided Image Collages N Jetchev, U Bergmann, G Yildirim NeurIPS 2019 Workshop on Machine Learning for Creativity and Design, 2019 | 5 | 2019 |
| Set flow: A permutation invariant normalizing flow K Rasul, I Schuster, R Vollgraf, U Bergmann arXiv preprint arXiv:1909.02775, 2019 | 5 | 2019 |
| Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Image Stylization N Jetchev, U Bergmann, G Yildirim 32nd Conference on Neural Information Processing Systems (NIPS 2018 …, 2018 | 4 | 2018 |
| Ontogenesis of invariance transformations U Bergmann, C von der Malsburg Computational and Systems Neuroscience (Cosyne), 2008 | 4 | 2008 |
Nikolay JetchevSenior Research Scientist at ZalandoVerified email at zalando.de
