In this story, DenseNet (Dense Convolutional Network) is reviewed. This is the paper in 2017 CVPR which got Best Paper Award with over 2000…

Both the Inception and Residual networks are SOTA architectures, which have shown very good performance with relatively low computational…

In this part-2/2 of blog post we will explore the optimal functions used in skip-connections of ResNet blocks. Discuss the ResNeXt…

A curated list of awesome self-supervised methods. Contribute to jason718/awesome-self-supervised-learning development by creating an account on GitHub.

In this post, we'll explain how to initialize neural network parameters effectively. Initialization can have a significant impact on convergence in training deep neural networks...

What are outliers and how to deal with them?

Course Website & Materials: https://kuleshov-group.github.io/aml-website/ Lecture Notes: https://kuleshov-group.github.io/aml-book/intro.html Course Material...

Technical tutorials, Q&A, events — This is an inclusive place where developers can find or lend support and discover new ways to contribute to the community.

Backpropagation in convolutional neural networks. A closer look at the concept of weights sharing in convolutional neural networks (CNNs) and an insight on how this affects the forward and backward propagation while computing the gradients during training.