You can see this repo as a consolidation of reading groups which I do between me and myself :)
Keeping the pace of current Deep Learning Research is almost impossible and even focusing on a specific field, like Computer Vision, is extremely hard because of the new papers rate (which by the way I think it is a great thing, it makes us living in exciting times), their hard to understand content and the fact code is not so often accompanying the paper
This is specifically true if you are student as, in my opinion, the gap between the educational material (books, courses, ...) and the research material today is quite big.
The goal of this repo is to try helping students to make the quantum leap to get from the students side to the researchers side with the following methodology
- Selecting relevant or interesting papers
- Providing papers summaries
- Adding code snippets implementing specific parts
- Diving a bit more into theory and math when necessary (research papers tend to be vague on this kind of things)
As explained in Contribute.md contribution are absolutely welcome
-
Open issues to
- bugfix: notify me about bugs, typos, ...
- features: suggest relevant papers, discuss content, ...
-
Submit PR with new summaries, implementations, ...
Feel free to DM me on Twitter at @NicolaBernini to discuss anything
The content is typically Markdown because it is very light but as you know GitHub does not support server side math rendering so I suggest to use some Browser Plugin like
Tax All The Things
MathJax Plugin for GitHub
| Date | Topic | Content |
|---|---|---|
| 2020-10-11 | RL Framework - Visual see above | Added in the ReinforcementLearning section |
| 2020-08-24 | Focusing on the Deep Learning Code Development Challenges | Added Challenges in Deep Learning Code Development |
| 2020-08-17 | From Papers to Code: implementing Yolo v1 from the paper | Showing how to read a paper defining an architecture and how to implement the architecture directly in Pytorch |
| 2020-08-16 | Added Kanban Secion | In this Kanban I am going to collect interesting bookmarks related to papers and blog posts to read |
| 2020-08-15 | Added WorkingOn Section where I am happy to share papers and blog posts which I am currently reading | Started reading this interesting post from Adam Kosiorek Blog about ML of Sets |
| 2020-08-14 | Added section about Domain Adaptation with good first paper analysis | Universal Domain Adaptation through Self Supervision  |
| 2020-07-31 | Added Analysis of a New Paper | Analysis of An Optimistic Perspective on Offline Reinforcement Learning - Gist |
| 2020-07-10 | Added anew Section on GNN | Started the new Section about GNN with a paper summary Discovering Symbolic Models from Deep Learning with Inductive Biases Also available on Colab as Discovering Symbolic Models from Deep Learning with Inductive Biases |
| 2020-06-21 | Disentangled Representation | Commented Disentangling by Factorising on Scirate |
| 2020-04-18 | Causality and Machine Learning | Added related comments here #33 |
| 2020-02-24 | Domain Adaptation | Paper Read - Universal Domain Adaptation through Self Supervision #32 |
https://github.com/NicolaBernini/PapersAnalysis/issues
| Title | Authors | Link |
|---|---|---|
| Complex-YOLO Paper - Intro - Analysis | Valeo GmbH, Ilmenau University of Technology | #1 |
| PointNet | Stanfaord | #5 |
| Title | Authors | Link |
|---|---|---|
| Representation Learning | Goodfellow, Bengio, Courville - Deep Learning Book | #25 |
| Title | Authors | Link |
|---|---|---|
| Reinforcement Learning, Fast and Slow | DeepMind | #20 |
Commented Disentangling by Factorising on Scirate
- Updates in Reinforcement Learning
Added Reinforcement Learning, Fast and Slow notes
- Removed the PDF with a Collaborative Analysis Doc on Reinforcement Learning, fast and slow with comments open
Added Keras in depth tutorial - MNIST and CNN focused less on the how-to and more on the why and what happens under the hood
- feel free to comment on the Medium Version
Added Summary and Notes - Work in Progress about Andrew Zisserman Talk about Self Supervised Learning - 2018
Added Summary and Notes - Work in Progress about Daniel Roy's talk at ICML 2019
Added a Paper Readthrough Issue related to Reinforcement Learning, Fast and Slow paper from DeepMind
Added a PR about Reservoir Computing started with some Basic Elements elements
Added PR related to a new Paper Summary regarding CNN Debugging with Heatmaps
Added a Paper Readthrough Issue related to Quantum reservoir processing : very interesting Quantum Machine Learning paradigm
Added a PR about Geometric Deep Learning starting with Gauge Equivariant CNN paper summary
Added a PR about Fake News starting with a Paper Summary
Added a PR about Statistics and the first summary regards Variational Bayesian Monte Carlo also published as Kaggle Kernel
Added a PR to add D2 Net Summary
Added a PR to define the CNN in Computer Vision - Section starting with a Paper Summary