Semantic segmentation labels are expensive and time consuming to acquire...
Dense retrieval has been shown to be effective for retrieving relevant
d...
Self-attention has the promise of improving computer vision systems due ...
We present BoTNet, a conceptually simple yet powerful backbone architect...
Recently Transformer and Convolution neural network (CNN) based models h...
Medical images such as 3D computerized tomography (CT) scans and patholo...
Convolutions are a fundamental building block of modern computer vision
...
Grammatical Error Correction (GEC) has been recently modeled using the
s...
Batch-splitting (data-parallelism) is the dominant distributed Deep Neur...
We describe an approach to Grammatical Error Correction (GEC) that is
ef...
Deep neural networks with discrete latent variables offer the promise of...
The past year has witnessed rapid advances in sequence-to-sequence (seq2...
Tensor2Tensor is a library for deep learning models that is well-suited ...
Image generation has been successfully cast as an autoregressive sequenc...
Image generation has been successfully cast as an autoregressive sequenc...
Deep learning yields great results across many fields, from speech
recog...
The dominant sequence transduction models are based on complex recurrent...