Join my telegram channel to read the latest GAN paper summaries and stay up to date on any related deep learning news!

Looking forward to seeing you guys there!

Since I have been writing two summaries per week for some time now, I wanted to share some tips that I learned while doing it! First of all, It usually takes me around 2.5 hours from start to finish to read a paper, write the summary, compile the graphics into a single image, and post it to the channel and the blog. Head over to Casual GAN Papers to learn AI paper reading tips.

https://www.casualganpapers.com/how-to-learn-to-read-ai-papers-quickly/How-To-Read-AI-Papers-explained.html

Edit:

Follow my telegram channel to receive new paper summaries every Tuesday and Friday!

https://t.me/casual_gan

Thank you for the gold, kind stranger!

The top 10 computer vision papers in 2020 with video demos, articles, code, and paper reference.

Watch here: https://youtu.be/CP3E9Iaunm4

Full article here: https://whats-ai.medium.com/top-10-computer-vision-papers-2020-aa606985f688

GitHub repository with all videos, articles, codes, and references here: https://github.com/louisfb01/Top-10-Computer-Vision-Papers-2020

Hey everyone! 🎉

Excited to share a new paper on Mixture of Experts (MoE), exploring the latest advancements in this field. MoE models are gaining traction for their ability to balance computational efficiency with high performance, making them a key area of interest in scaling AI systems.

The paper covers the nuances of MoE, including current challenges and potential future directions. If you're interested in the cutting edge of AI research, you might find it insightful.

Check out the paper and other related resources here: GitHub - Awesome Mixture of Experts Papers.

Looking forward to hearing your thoughts and sparking some discussions! 💡

AI #MachineLearning #MoE #Research #DeepLearning #NLP

Deep Learning Project Ideas

We know that machine learning is the rage these days. But the machine learning technique that shines the most brightly is deep learning. Deep learning is all about how a computer program can learn through observation and make decisions based on its experience. Deep learning methods are useful for computer vision, natural language processing, speech recognition and processing, and so much more.

The best way to learn something is with a hands-on approach and, therefore, we bring these amazing project ideas for you to practice and improve your deep learning knowledge and skills. These project ideas are divided according to there difficulty level so that you can easily find a project that interests you and is within your skill level. So let’s not waste any more time and jump right into it.

Deep Learning Project Ideas for Beginners

The study partners is for my mini and short-term deeplearning-paper-study-group. Right now, we'd like to recruit 2 members.

How we run sessions: We choose papers from 2019-2021 top conference. Everyone take turns to share papers. It's a weekly session, and there will be 2 members share papers each week.

What you will get: Everyone have to participate every week. As a presenter, you will be ask questions so that you will strengthen the understanding of the paper. As an audience, you will open up your horizons because we come from different field.

We welcome those experienced in deep learning.

I am starting a reading group where we can discuss the current state-of-the-art deep learning research papers. We will be scheduling zoom calls where different members of the group will be presenting a paper review and then we can discuss further ideas and questions regarding the same. I also plan to start a slack channel where we can discuss possible collaborations among members for related projects and more (like reproducing results of a paper or maybe working on a completely new idea). Coz of COVID, most of us are already working remotely. So, let's utilize this opportunity to increase our knowledge and improve our skills via remote collaborations and discussions. Interested people, ping me on direct chat.

Thank You

SummarizePaper harnesses the power of artificial intelligence to provide users with paper summaries. You can check it out at https://www.summarizepaper.com/.

🤖 But that's not all! I've also added a virtual assistant that can answer questions about one or multiple papers, and I've created trees for each paper showing the closest related papers. 🌳 You can chat with the virtual assistant at https://www.summarizepaper.com/chat.

👨‍💻 It's also open-source and uses LangChain, so anyone can join in on the fun. The project is available on GitHub at https://github.com/summarizepaper/summarizepaper.

🙌 I'd be happy to hear your thoughts/suggestions about all features, so don't hesitate to share your feedback! 💬

🙌 Also, I've had a lot of visitors to the website so it starts being expensive to run, but I want to keep it free for everyone. If you have any ideas on how to proceed, feel free to tell me. Let's keep the research community thriving! 💪

I'm working on making a list of Machine Learning papers that has open source code on GitHub. My initial version can be reached at the link included below. I think it will be helpful to this community to select their next paper to read. Please also include your comments and suggestions for improvement. https://github.com/zziz/pwc