dieter1955 / __init__

Introduction

MLT __init__ is a monthly event led by Jayson Cunanan and J. Miguel Valverde where, similarly to a traditional journal club, a paper is first presented by a volunteer and then discussed among all attendees. Our goal is to give participants good initializations to effectively study and improve their understanding of Deep Learning. We will try to achieve this by:

• Discussing fundamental papers, whose main ideas are currently implemented on state-of-the-art models.
• Providing the audience with summaries, codes and visualizations to help understand the critical parts of a paper.

Sessions

Date	Topic	Paper	Presenter	Video
10/Jan/2021	CV: Separable Convolutions	Xception	Jayson Cunanan
14/Feb/2021	CV: Dilated Convolutions + ASPP	DeepLabv2	J. Miguel Valverde
14/Mar/2021	CV: Attention in Images	Squeeze and Excitation	Alisher Abdulkhaev
11/Apr/2021	CV: Attention in GANs	SAGAN	Mayank Bhaskar
9/May/2021	NLP: Attention	RNN encoder–decoder for SMT	Ana Valeria
13/Jun/2021	NLP: Attention	Sequence to Sequence Learning with Neural Networks	Charles Melby-Thompson

Sessions will be held via Zoom starting at 5pm (JST) / 9am (CET). Check at what time is in your region here.

Format

Introduction (5min) + Paper presentation (25min) + Discussion (60min)

The introduction and paper presentation will be recorded (if agreed with the presenter) whereas the discussion will not be recorded. This format allows participants to interact during the discussion while protecting their privacy.

For participants

As most of the time is allocated for discussion, we kindly ask participants to read the paper in advance and to join the session with at least two questions or comments in mind. These questions/comments can be to highlight interesting or unclear parts. For instance: what did you like the most about this paper? What did you learn? What did you not understand?

To make the session more interactive, participants can also ask questions during the presentation. We encourage everyone to use their microphone, but please keep in mind the environmental noise. If you cannot use your microphone or you want to keep your privacy, you are welcome to write in the Zoom chat or Slack channel, and either Jayson or Miguel will read your questions aloud.

For presenters

Inline with the goals of MLT __init__, we encourage presenters to incorporate intuitive visualizations and code in Powerpoint/Slides presentations, Jupyter notebooks (+ Colab), or any other format or platform. If possible, we would like to make this material publicly available in this repository.

Code of Conduct

As this event aims to be interactive, please remember to be kind and respectful to each other. Full code of conduct here.

We want your feedback!

Feedback and contact form: https://forms.gle/jJLWyAMjjVKL8KFRA