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

Admin: @HusseinSheikho || @Hussein_Sheikho
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📑 Big data and artificial intelligence in cancer research

📕 Journal:  Trends in Cancer (🔥 I.F.= 18.4)
🗓 Publish year: 2023

📱 Authors: Xifeng Wu, Wenyuan Li, Huakang Tu
🏢 University: Zhejiang University School of Medicine, China

📎 Study the paper

https://news.1rj.ru/str/DataScienceT ⚙️
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🐱 Moving Object Segmentation:All You Need Is SAM (and Flow)

SAM + Optical Flow = FlowSAM

FlowSAM is a new tool for detecting and segmenting moving objects in video, which significantly outperforms all previous models , both for a single object and for multiple objects 🔥

Project page: https://www.robots.ox.ac.uk/~vgg/research/flowsam/

Code: https://github.com/video2game/video2game

Paper: https://arxiv.org/abs/2404.12389

Data: https://drive.google.com/drive/folders/1tmDq_vG_BvY5po40Ux5OBds1avUM_CbR

https://news.1rj.ru/str/DataScienceT ⚙️
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📁 Machine Learning and Health Science Research: Tutorial

📕 Journal: Journal of Medical Internet Research (I.F.= 7.4)
🗓 Publish year: 2024

📱 Authors: Hunyong Cho, Jane She, Daniel De Marchi, ...
🏢 University: University of North Carolina at Chapel Hill, United States

📎 Study the paper
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🗣 OpenVoice V2 - a Text-to-Speech model that can clone any voice and speak in any language.

OpenVoice V2 is a new version of the open text-to-speech model that allows you to clone any voice and generate speech in various languages.

Github: https://github.com/myshell-ai/OpenVoice/tree/main
Usage: https://github.com/myshell-ai/OpenVoice/blob/main/docs/USAGE.md
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🖼 HiDiffusion: Unlocking High-Resolution Creativity and Efficiency in Low-Resolution Trained Diffusion Models 🦊

A new training-free method that improves the performance of pre-trained diffusion models.

It can be integrated into diffusion pipelines by adding just one line of code!

pip3 install hidiffusion


page : https://hidiffusion.github.io
paper : https://arxiv.org/abs/2311.17528
code : https://github.com/megvii-research/HiDiffusion
colab : https://colab.research.google.com/drive/1EiBn9lSnPZTU4cikRRaBBexs429M-qty?usp=sharing

https://news.1rj.ru/str/DataScienceT ⚙️
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🔥 FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent

Massachusetts Institute of Technology introduced FlowMap.

This is a new comprehensive differentiable method for reconstructing a 3D scene , which allows you to accurately specify camera angles, motion characteristics and video depth for each frame.

FlowMap allows you to create realistic 360° views.

Github: https://github.com/dcharatan/flowmap
Paper: https://arxiv.org/abs/2404.15259
Dataset: https://drive.google.com/drive/folders/1PqByQSfzyLjfdZZDwn6RXIECso7WB9IY

https://news.1rj.ru/str/DataScienceT ⚙️
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OpenBioLLM-Llama3-70B and 8B: Open-source Large Language Models in Medical Domain

OpenBioLLM-Llama3-70B and 8B: the most effective and affordable Lms in the medical field today! 🩺 💊 🧬

Outperforms industry giants like GPT-4, Gemini, Meditron-70B, Med-PaLM-1 and Med-PaLM-2 in the biomedical field. 🏥 📈 ⭐️

The OpenBioLLM-70B reaches SOTA and is a new achievement for models of this size.
The OpenBioLLM-8B even outperforms GPT-3.5, Gemini and Meditron-70B! 🚀

- 70B : https://huggingface.co/aaditya/OpenBioLLM-Llama3-70B

- 8B : https://huggingface.co/aaditya/OpenBioLLM-Llama3-8B

- Medical Leaderboard : https://huggingface.co/spaces/openlifescienceai/open_medical_llm_leaderboard
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📃Graph Machine Learning in the Era of Large Language Models (LLMs)

🗓 Publish year: 2023

🧑‍💻Authors: Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li

🏢Universities: The Hong Kong Polytechnic University,Michigan State University, North Carolina State University

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⭐️ The PyTorch team is developing a library for learning LLM called torch titan.

Today the library has become publicly available on GitHub, but it is still in a pre-release state and is actively being developed.

- Library link: https://github.com/pytorch/torchtitan

- Tutorial on working with torch titan: https://www.youtube.com/watch?v=ee5DOEqD35I

The library was created for preliminary training of models, and for fine tuning PyTorch has another library, torchtune:
https://github.com/pytorch/torchtune

https://news.1rj.ru/str/DataScienceT ⚙️
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MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition

🖥 Github: https://github.com/zeroqiaoba/mertools

📕 Paper: https://arxiv.org/abs/2404.17113v1

🔥 Dataset: https://paperswithcode.com/dataset/voxceleb2


https://news.1rj.ru/str/DataScienceT 💋
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⚡️ Arena-Hard is an evaluation tool for instruction-tuned LLMs.

Arena-Hard - Creating High Quality Tests for LLM Assessment

Arena-Hard allows you to evaluate LLM responses using 7 specific metrics; criteria in the image

▶️ More about Arena-Hard
🖥 GitHub

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