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Grid Partitioned Attention: Efficient TransformerApproximation with Inductive Bias for High Resolution Detail Generation



Nikolay Jetchev , Gökhan Yildirim , Christian Bracher , Roland Vollgraf

* code available at https://github.com/zalandoresearch/gpa 

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Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting



Kashif Rasul , Calvin Seward , Ingmar Schuster , Roland Vollgraf


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CRISP: A Probabilistic Model for Individual-Level COVID-19 Infection Risk Estimation Based on Contact Data



Ralf Herbrich , Rajeev Rastogi , Roland Vollgraf


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Multi-variate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows



Kashif Rasul , Abdul-Saboor Sheikh , Ingmar Schuster , Urs Bergmann , Roland Vollgraf


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Set Flow: A Permutation Invariant Normalizing Flow



Kashif Rasul , Ingmar Schuster , Roland Vollgraf , Urs Bergmann


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Generating High-Resolution Fashion Model Images Wearing Custom Outfits



Gökhan Yildirim , Nikolay Jetchev , Roland Vollgraf , Urs Bergmann

* Accepted to the International Conference on Computer Vision, ICCV 2019, Workshop on Computer Vision for Fashion, Art and Design 

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A Deep Learning System for Predicting Size and Fit in Fashion E-Commerce



Abdul-Saboor Sheikh , Romain Guigoures , Evgenii Koriagin , Yuen King Ho , Reza Shirvany , Roland Vollgraf , Urs Bergmann

* Published at the Thirteenth ACM Conference on Recommender Systems (RecSys '19), September 16--20, 2019, Copenhagen, Denmark 

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Learning Set-equivariant Functions with SWARM Mappings



Roland Vollgraf


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A Bandit Framework for Optimal Selection of Reinforcement Learning Agents



Andreas Merentitis , Kashif Rasul , Roland Vollgraf , Abdul-Saboor Sheikh , Urs Bergmann

* Published at the 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montreal, Canada. Deep Reinforcement Learning Workshop 

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