papers-we-read

Is an initiative to motivate club members to read about the latest advancements in technologies that shape the world around us. This repo houses summaries for exciting works in the field of Machine Learning and Deep Learning.

Contributing

Papers on all related fields are welcome, we love to read and learn things related to (well articifical ones) neurons here 😀

Template

paper_title

Author 1, Author 2, ...,year_of_publication

Summary

Include a brief description about the paper from an intuitive point of view if possible. Basically what's new about this !

Method

A comprehensive description of the methodology proposed.
Include images for better presentation.
Add mathematical equations for better understanding.

Results

Comments on the results in the paper.
Comparisons with the baselines and existing State Of The Art.

Two-Cents

Your personal opinion about the paper including appreciations, criticism and possible future directions for research.

Resources

Links to the project page, youtube video, implementation, blog, etc. for enthusiasts to explore.

How to Open a PR (Pull Request)

Fork and Pull the latest papers_we_read.
Checkout to a new branch with the name PAPER_TITLE.

Please do not use master branch for changes to the repo !
Commit your summaries on the new branch on your forked repo
Create a PR with the title: Add Summary for PAPER_TITLE

Guidelines

Add the animations, images, graphs etc used in the images folder
If you are out of ideas, the standard template might be of your help, although you are free encourage and choose whatever suits your style.
Credit the original authors

BitByte-TPC/papers-we-read

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