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11/25/2021
Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations
A classical problem in computer vision is to infer a 3D scene representa...
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06/18/2021
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
Vision Transformers (ViT) have been shown to attain highly competitive p...
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05/04/2021
MLP-Mixer: An all-MLP Architecture for Vision
Convolutional Neural Networks (CNNs) are the go-to model for computer vi...
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04/07/2021
Differentiable Patch Selection for Image Recognition
Neural Networks require large amounts of memory and compute to process h...
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10/22/2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
While the Transformer architecture has become the de-facto standard for ...
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10/20/2020
Towards End-to-End In-Image Neural Machine Translation
In this paper, we offer a preliminary investigation into the task of in-...
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10/29/2019
An Empirical Study of Generation Order for Machine Translation
In this work, we present an empirical study of generation order for mach...
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06/06/2019
Scaling Autoregressive Video Models
Due to the statistical complexity of video, the high degree of inherent ...
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06/04/2019
KERMIT: Generative Insertion-Based Modeling for Sequences
We present KERMIT, a simple insertion-based approach to generative model...
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02/08/2019
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
We present the Insertion Transformer, an iterative, partially autoregres...
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11/07/2018
Blockwise Parallel Decoding for Deep Autoregressive Models
Deep autoregressive sequence-to-sequence models have demonstrated impres...
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09/12/2018
An Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation
Music relies heavily on self-reference to build structure and meaning. W...
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09/12/2018
Music Transformer
Music relies heavily on repetition to build structure and meaning. Self-...
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07/10/2018
Universal Transformers
Self-attentive feed-forward sequence models have been shown to achieve i...
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03/16/2018
Tensor2Tensor for Neural Machine Translation
Tensor2Tensor is a library for deep learning models that is well-suited ...
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03/09/2018
Fast Decoding in Sequence Models using Discrete Latent Variables
Autoregressive sequence models based on deep neural networks, such as RN...
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03/06/2018
Self-Attention with Relative Position Representations
Relying entirely on an attention mechanism, the Transformer introduced b...
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02/15/2018
Image Transformer
Image generation has been successfully cast as an autoregressive sequenc...
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02/15/2018
Image Tranformer
Image generation has been successfully cast as an autoregressive sequenc...
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06/16/2017
One Model To Learn Them All
Deep learning yields great results across many fields, from speech recog...
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06/12/2017
Attention Is All You Need
The dominant sequence transduction models are based on complex recurrent...
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04/15/2017
Neural Paraphrase Identification of Questions with Noisy Pretraining
We present a solution to the problem of paraphrase identification of que...
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11/06/2016
Hierarchical Question Answering for Long Documents
We present a framework for question answering that can efficiently scale...
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06/06/2016