resources

RNN & LSTM:

• CS231n Recurrent Neural Networks notes
• Introduction to recurrent neural networks by Jeremy Jordan
• Understanding LSTM Networks by Christopher Olah

CNN:

• MIT: Machine Learning 6.036, Lecture 8: Convolutional neural networks (Fall 2020) by Tamara Brodrick

Diffusion Models:

• Understanding Diffusion Models: A Unified Perspective by Calvin Luo

Papers:

For me, a good paper is one that is easy to read and understand, while also imparting knowledge or answering a question.

• Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications
• EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
• Deep Residual Learning for Image Recognition