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Jessica Yung

3 accepted papers

2021

MLP-Mixer: An all-MLP Architecture for Vision

NeurIPS 2021poster

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 paper we show that while convolutions and attention are both sufficient for good performance, neither of them are necess…

2021

On Robustness and Transferability of Convolutional Neural Networks

CVPR 2021poster

Modern deep convolutional networks (CNNs) are often criticized for not generalizing under distributional shifts. However, several recent breakthroughs in transfer learning suggest that these networks can cope with severe distribution shifts and successfully adapt to new tasks from a few training exa…

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2020

Big Transfer (BiT): General Visual Representation Learning

ECCV 2020poster

Transfer of pre-trained representations improves sample efficiency and simplifies hyperparameter tuning when training deep neural networks for vision. We revisit the paradigm of pre-training on large supervised datasets and fine-tuning the model on a target task. We scale up pre-training, and propos…