In this edition of W&B’s Paper Reading Group we will look into the EfficientNetV2 paper in detail & learn all about it.
In the paper, the authors seek to establish a general recipe for training deep ResNets without normalization layers which achieve test accuracies competitive with state-of-the-art! Batch Normalization (BatchNorm) has been key in advancing deep learning research in computer vision, but in the past few years a new line of research has emerged that seeks to eliminate layers which normalize activations entirely.
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W&B’s Paper Reading Group is a biweekly, beginner-friendly space led by Aman Arora
Register:
📍
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Agenda:
0:00 Welcome and introduction
3:40 How to read a paper
7:13 EfficientNetV2 Paper
1:05:43 Q&A on the paper
Links
👉 EfficientNetV2 paper summary & comments:
👉 Nf-ResNets paper:
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