This page has 2 purposes: share some links that I was often referring to and share personal summaries of some papers that I have read and dived into.

Theses supervision

Time Consistency for automatic object detection

Explainable Pipeline Reinforcement Learning

Understanding differences in games' complexities

Neural Style Transfer

Interesting sources of information

I hereby refer to all nice source of information I usually use in order to get knowledge about machine learning, or any interesting topic. If you are interested in explanations about anything, made by performant video maker, please give a look at my Youtube following page.

Other nice sources of knowledge:

Machine Learning Blog Posts

Deadly Triad Issue of Reinforcement Learning

How to handle the Deadly Triad issue

Summaries of papers

For scientific paper summaries, my goal is to share complete summary with all important information that should be highlighted, with some comments. Nowadays, a “popularized” (explained for a less scientific audience) version of the scientific paper is usually provided (through blog posts for example). When it’s the case, I provide the link. The difference between my summaries and these block-posts is that I usually try to provide every relevant scientific information (i.e. math equations and links) for scientifically understand the paper.

This work was first personal, to better dive into the paper that I have found astonishing so far, but I have finally decided to share this work that could be useful also to others. I hope this could help some people that want to quickly read them.
All the credits have to be given to the amazing work made by the actual researchers and authors.