Here are the 3 most interesting research papers of the month, in case you missed any of them. It is a curated list of the latest breakthroughs in AI and Data Science by release date with a clear video explanation, link to a more in-depth article, and code (if applicable). Enjoy the read, and let me know if I missed any important papers in the comments, or by contacting me directly on LinkedIn!
50+ expert meteorologists assessed DeepMind's new model beating current nowcasting methods in 89% of situations for its accuracy and usefulness!
Read more and link to the code: https://hackernoon.com/ai-endorsed-by-expert-meteorologists-deepminds-weather-forecast-model
This AI takes a poorly calibrated audio clip, for example, a movie scene with the music way too loud and actors speaking quietly, and can simply turn up the speech and lower the music!
Read more and link to the code: https://hackernoon.com/this-ai-can-separate-speech-music-and-sound-effects-from-movie-soundtracks
An AI that takes images as inputs to generate smooth and high quality videos!
Read more and link to the code: https://hackernoon.com/this-ai-creates-videos-from-a-couple-of-images
If you’d like to read more research papers as well, I recommend you read my article where I share my best tips for finding and reading more research papers.
 Ravuri, S., Lenc, K., Willson, M., Kangin, D., Lam, R., Mirowski, P., Fitzsimons, M., Athanassiadou, M., Kashem, S., Madge, S. and Prudden, R., 2021. Skillful Precipitation Nowcasting using Deep Generative Models of Radar, https://www.nature.com/articles/s41586-021-03854-z.
 Petermann, D., Wichern, G., Wang, Z., & Roux, J.L. (2021). The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World Soundtracks. https://arxiv.org/pdf/2110.09958.pdf.
 Rückert, D., Franke, L. and Stamminger, M., 2021. ADOP: Approximate Differentiable One-Pixel Point Rendering. https://arxiv.org/pdf/2110.06635.pdf.