D
Dirk Weissenborn
Researcher at Google
Publications - 44
Citations - 15572
Dirk Weissenborn is an academic researcher from Google. The author has contributed to research in topics: Question answering & Recurrent neural network. The author has an hindex of 19, co-authored 40 publications receiving 2987 citations. Previous affiliations of Dirk Weissenborn include Dresden University of Technology & German Research Centre for Artificial Intelligence.
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy,Lucas Beyer,Alexander Kolesnikov,Dirk Weissenborn,Xiaohua Zhai,Thomas Unterthiner,Mostafa Dehghani,Matthias Minderer,Georg Heigold,Sylvain Gelly,Jakob Uszkoreit,Neil Houlsby +11 more
TL;DR: Vision Transformer (ViT) attains excellent results compared to state-of-the-art convolutional networks while requiring substantially fewer computational resources to train.
Proceedings Article
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy,Lucas Beyer,Alexander Kolesnikov,Dirk Weissenborn,Xiaohua Zhai,Thomas Unterthiner,Mostafa Dehghani,Matthias Minderer,Georg Heigold,Sylvain Gelly,Jakob Uszkoreit,Neil Houlsby +11 more
TL;DR: The Vision Transformer (ViT) as discussed by the authors uses a pure transformer applied directly to sequences of image patches to perform very well on image classification tasks, achieving state-of-the-art results on ImageNet, CIFAR-100, VTAB, etc.
Journal ArticleDOI
An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition
George Tsatsaronis,Georgios Balikas,Prodromos Malakasiotis,Ioannis Partalas,Matthias Zschunke,Michael R. Alvers,Dirk Weissenborn,Anastasia Krithara,Sergios Petridis,Dimitris Polychronopoulos,Yannis Almirantis,John Pavlopoulos,Nicolas Baskiotis,Patrick Gallinari,Thierry Artières,Axel-Cyrille Ngonga Ngomo,Norman Heino,Eric Gaussier,Liliana Barrio-Alvers,Michael Schroeder,Ion Androutsopoulos,Georgios Paliouras +21 more
TL;DR: Overall, BioASQ helped obtain a unified view of how techniques from text classification, semantic indexing, document and passage retrieval, question answering, and text summarization can be combined to allow biomedical experts to obtain concise, user-understandable answers to questions reflecting their real information needs.
Proceedings Article
Object-Centric Learning with Slot Attention
Francesco Locatello,Dirk Weissenborn,Thomas Unterthiner,Aravindh Mahendran,Georg Heigold,Jakob Uszkoreit,Alexey Dosovitskiy,Thomas Kipf +7 more
TL;DR: An architectural component that interfaces with perceptual representations such as the output of a convolutional neural network and produces a set of task-dependent abstract representations which are exchangeable and can bind to any object in the input by specializing through a competitive procedure over multiple rounds of attention is presented.
Posted Content
Axial Attention in Multidimensional Transformers
TL;DR: Axial Transformers is proposed, a self-attention-based autoregressive model for images and other data organized as high dimensional tensors that maintains both full expressiveness over joint distributions over data and ease of implementation with standard deep learning frameworks, while requiring reasonable memory and computation.