ML Research Hub – Telegram
ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

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🧑‍🎓 Machine learning approaches for personalized medicine

📕PhD Thesis from Università del Piemonte Orientale, Italy

🗓Publish year: 2024

📎 Study thesis

✅️ https://news.1rj.ru/str/DataScienceT ✅️
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😀 ViViD: Diffusion Virtual Try-ON 🧑‍🎓

👉 ViViD is a novel framework employing powerful diffusion models to tackle the task of video virtual try-on. Code announced, not released yet 😢

👉 Review: https://t.ly/h_SyP

👉 Paper: arxiv.org/pdf/2405.11794

👉 Repo: https://lnkd.in/dT4_bzPw

👉 Project: https://lnkd.in/dCK5ug4v

✅️ https://news.1rj.ru/str/DataScienceT ✅️
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🌹 Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control

🤯 Face Adapter is something!

🚀 New powerful face transfer adapter that works with pre-trained diffusion models.

🔄 Provides precise control over facial expressions and features.

Works with video and photos.

🟢 Github: https://github.com/FaceAdapter/Face-Adapter

🟢 Paper: https://arxiv.org/abs/2405.12970

🟢 HF: https://huggingface.co/FaceAdapter/FaceAdapter

🟢 Project: https://faceadapter.github.io/face-adapter.github.io/

✅️ https://news.1rj.ru/str/DataScienceT ✅️
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🧰 A comprehensive toolbox of data scientists
Access to 500+ TB of data science content

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⚡️ Adobe has released DMD2!

A new and improved distillation method that can turn diffusion models such as SDXL into powerful one-step image generators.

It's been a while since we've seen any interesting updates to the SD ecosystem, so this is cool 🔥

Project page: https://tianweiy.github.io/dmd2/

Code: https://github.com/tianweiy/DMD2

Demo: https://4e4a5c6a8b08f76802.gradio.live

🌐 http://t.me/codeprogrammer ✅️
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🎓 Empowering Graph Neural Networks for Real-World Tasks

📘 Doctoral thesis
🗓 Publish year: 2024

🧑‍💻 Author: Zhichun Guo
🏢 University: University of Notre Dame, Indiana

📎 Study Thesis 

🌐 http://t.me/codeprogrammer ✅️
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Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI

🖥 Github: https://github.com/935963004/labram

📕Paper: https://arxiv.org/abs/2405.18765v1

#machineLearning

https://news.1rj.ru/str/DataScienceT
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🌟 InstaDrag: complex image editing (rotating in space, changing shape, etc.) using simple gestures

InstaDrag is an approach that allows you to edit an image using a simple drag gesture in ~1 second.
At the same time, InstaDrag also copes with complex deformations of part of the image that are not represented in the training data (such deformations are, for example, elongation of hair, curvature of the rainbow, etc.).
There are plans to integrate InstaDrag with SDXL in the future

🖥 GitHub
🟡 InstaDrag page
🟡 Arxiv

https://news.1rj.ru/str/DataScienceT
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⚡️ Flash version of Scribble SDXL

Utilizes SDXL Flash and Scribble SDXL, making it even faster to get quality images from simple sketches and doodles

🤗 Launch on Hugging Face

https://news.1rj.ru/str/DataScienceT
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