The PRoteomics IDEntifications (PRIDE) database ( https://www.ebi.ac.uk/pride/ ) is the
world’s largest data repository of mass spectrometry-based proteomics data, and is one of the …

Convolutional Neural Networks (CNNs) are the go-to model for computer vision. Recently,
attention-based networks, such as the Vision Transformer, have also become popular. In this …

… 𝒌 𝒋 𝒗 𝒋 … 𝒌 𝒋,𝟐 𝒌 𝒋,𝟏 𝒗 𝒋,𝟐 𝒗 𝒋,𝟏 …

While the Transformer architecture has become the de-facto standard for natural language
processing tasks, its applications to computer vision remain limited. In vision, attention is …

The dominant sequence transduction models are based on complex recurrent orconvolutional
neural networks in an encoder and decoder configuration. The best performing such …

… ) is the associated Wikipedia document, and a (i) is a vector with components a j ( i ) for j =
1 … 5. Each a j ( i ) is the output from the j’th annotator, and can be a paragraph in d (i) , or can …

The amount of public proteomics data is rapidly increasing but there is no standardized format
to describe the sample metadata and their relationship with the dataset files in a way that …

Relying entirely on an attention mechanism, the Transformer introduced by Vaswani et al. (2017)
achieves state-of-the-art results for machine translation. In contrast to recurrent and …

We propose a simple neural architecture for natural language inference. Our approach uses
attention to decompose the problem into subproblems that can be solved separately, thus …

Image generation has been successfully cast as an autoregressive sequence generation or
transformation problem. Recent work has shown that self-attention is an effective way of …