Roland Vollgraf
Roland Vollgraf
Zalando Research
Verified email at - Homepage
Cited by
Cited by
Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms
H Xiao, K Rasul, R Vollgraf
arXiv preprint arXiv:1708.07747, 2017
Contextual string embeddings for sequence labeling
A Akbik, D Blythe, R Vollgraf
Proceedings of the 27th International Conference on Computational …, 2018
Quadratic optimization for simultaneous matrix diagonalization
R Vollgraf, K Obermayer
IEEE Transactions on Signal Processing 54 (9), 3270-3278, 2006
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
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
Texture synthesis with spatial generative adversarial networks
N Jetchev, U Bergmann, R Vollgraf
arXiv preprint arXiv:1611.08207, 2016
From grids to places
M Franzius, R Vollgraf, L Wiskott
Journal of computational neuroscience 22 (3), 297-299, 2007
Learning texture manifolds with the periodic spatial GAN
U Bergmann, N Jetchev, R Vollgraf
arXiv preprint arXiv:1705.06566, 2017
Fashion DNA: merging content and sales data for recommendation and article mapping
C Bracher, S Heinz, R Vollgraf
arXiv preprint arXiv:1609.02489, 2016
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
Fashion-mnist: A novel image dataset for benchmarking machine learning algorithms. arXiv 2017
H Xiao, K Rasul, R Vollgraf
arXiv preprint arXiv:1708.07747, 0
Multi dimensional ICA to separate correlated sources
R Vollgraf, K Obermayer
Advances in neural information processing systems, 993-1000, 2002
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
Nonlinear filtering of electron micrographs by means of support vector regression
R Vollgraf, M Scholz, IA Meinertzhagen, K Obermayer
Advances in Neural Information Processing Systems, 717-724, 2004
An LSTM-based dynamic customer model for fashion recommendation
S Heinz, C Bracher, R Vollgraf
arXiv preprint arXiv:1708.07347, 2017
Sparse optimization for second order kernel methods
R Vollgraf, K Obermayer
The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006
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
Generating high-resolution fashion model images wearing custom outfits
G Yildirim, N Jetchev, R Vollgraf, U Bergmann
Proceedings of the IEEE International Conference on Computer Vision …, 2019
Convolutive decorrelation procedures for blind source separation
R Vollgraf, M Stetter, K Obermayer
Proceedings of the 2. International Workshop on ICA, Helsinki, 515-520, 2000
Blind source separation of single components from linear mixtures
R Vollgraf, I Schieβl, K Obermayer
International Conference on Artificial Neural Networks, 509-514, 2001
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