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.

This class will provide a solid introduction to the field of RL. Students will learn about the core challenges and approaches in the field, including general...

We propose an algorithm for meta-learning that is model-agnostic, in the sense that it is compatible with any model trained with gradient descent and applicable to a variety of different learning...