An off-the-shelf robust classifier can be used to perform a range of computer vision tasks beyond classification.

Networks that can already (sort of) perform tasks with random weights.

Bayesian Deep Learning Benchmarks. Contribute to OATML/bdl-benchmarks development by creating an account on GitHub.

A collection of various deep learning architectures, models, and tips - rasbt/deeplearning-models

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Artificial Intelligence in Healthcare is revolutionizing the medical industry by providing a helping hand. This Edureka session will help…

Convolutions are a fundamental building block of modern computer vision systems. Recent approaches have argued for going beyond convolutions in order to capture long-range dependencies. These...

The 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) kicked off today in Long Beach, California. CVPR is one of the world’s top three academic conferences in the field of computer vision (along with ICCV and ECCV). A total of 1300 papers…

Adapters obtain comparable results to BERT on several NLP tasks while achieving parameter efficiency.

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This Edureka session will help you understand all about Boosting Machine Learning and boosting algorithms and how they can be implemented to increase the efficiency…

Data augmentation is a critical component of training deep learning models. Although data augmentation has been shown to significantly improve image classification, its potential has not been...

Posted by Alex Fabrikant, Research Scientist, Google Research Hundreds of millions of people across the world rely on public transit for their da...