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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πŸ–₯ StackFLOW: Monocular Human-Object Reconstruction by Stacked Normalizing Flow with Offset.

πŸ–₯ Github: https://github.com/huochf/StackFLOW

πŸ“• Paper: https://arxiv.org/abs/2407.20545v1

πŸš€ Dataset: https://paperswithcode.com/dataset/behave

https://t.me/DataScienceT ⭐️
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This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

βœ… https://t.me/addlist/8_rRW2scgfRhOTc0

βœ… https://t.me/Python53
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πŸ‘¨πŸ»β€πŸ’» Have you ever thought about what makes artificial intelligence projects and machine learning models work better and smarter? The answer is simple: quality data!

βœ… Now with MagPie-Ultra, the first synthetic dataset created by Llama 3.1 405B-Instruct advanced artificial intelligence model, you have a ready, high-quality and diverse dataset for training and improving artificial intelligence models , which can make your projects more accurate and smarter and reach Help for better results.πŸ‘‡

β”Œ πŸ’Έ MagPie-Ultra
β”œ
πŸ–₯ Pipeline
β””
πŸ’° Dataset

🌐 https://t.me/DataScienceT ⭐️
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🎁 Your balance is credited $4,000 , the owner of the channel wants to contact you!

Dear subscriber, we would like to thank you very much for supporting our channel, and as a token of our gratitude we would like to provide you with free access to Lisa's investor channel, with the help of which you can earn today

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No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation

πŸ’» Github: https://github.com/themody/no-learning-rates-needed-introducing-salsa-stable-armijo-line-search-adaptation

πŸ“• Paper: https://arxiv.org/abs/2407.20650v1

✈️ Dataset: https://paperswithcode.com/dataset/cifar-10

🌐 https://t.me/DataScienceT ⭐️
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🌟 VADER – video diffusion alignment via reward gradient

VADER is a method for aligning the results of diffusion models for video generation;
VADER allows to improve various models such as VideoCrafter, OpenSora, ModelScope and StableVideoDiffusion using different approaches such as HPS, PickScore, VideoMAE, VJEPA, YOLO, Aesthetics and others.

πŸ–₯ GitHub
🟑 VADER page

🌐 https://t.me/DataScienceT ⭐️
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DeepInteraction & DeepInteraction++

πŸ–₯ Github: https://github.com/fudan-zvg/deepinteraction

πŸ“• Paper: https://arxiv.org/abs/2408.05075v1

πŸš€ Dataset: https://paperswithcode.com/dataset/nuscenes
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Paper Name: The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Paper: https://arxiv.org/pdf/2408.06292v2.pdf

Code: https://github.com/sakanaai/ai-scientist

🌐 https://t.me/DataScienceT ⭐️
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Zero-Shot Surgical Tool Segmentation in Monocular Video Using Segment Anything Model 2

Paper: https://arxiv.org/pdf/2408.01648v1.pdf

Code: https://github.com/AngeLouCN/SAM-2_Surgical_Video

https://t.me/DataScienceT ⭐️
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MooER: LLM-based Speech Recognition and Translation Models from Moore Threads

Paper: https://arxiv.org/pdf/2408.05101v1.pdf

Code: https://github.com/moorethreads/mooer

Datasets: https://github.com/kaldi-asr/kaldi/tree/master/egs/aishell2

https://t.me/DataScienceT ⭐️
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UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling

Paper: https://arxiv.org/pdf/2408.04810v1.pdf

Code: https://github.com/facebookresearch/unibench

Datasets: https://www.cs.toronto.edu/~kriz/cifar.html

https://t.me/DataScienceT ⭐️
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MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Paper: https://arxiv.org/pdf/2408.02900v1.pdf

Code: https://github.com/UCSC-VLAA/MedTrinity-25M

Datasets: https://yunfeixie233.github.io/MedTrinity-25M/

https://t.me/DataScienceT ⭐️
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DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

Paper: https://arxiv.org/pdf/2408.08152v1.pdf

Code: https://github.com/deepseek-ai/deepseek-prover-v1.5

Datasets: https://github.com/zhangir-azerbayev/ProofNet

https://t.me/DataScienceT ⭐️
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Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment Perspective

Paper: https://arxiv.org/pdf/2408.08228v1.pdf

Code: https://github.com/zx-pan/medanomalydetection-iqa

Datasets: http://braintumorsegmentation.org/ || https://brain-development.org/ixi-dataset/

https://t.me/DataScienceT ⭐️
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MambaMIM: Pre-training Mamba with State Space Token-interpolation

Paper: https://arxiv.org/pdf/2408.08070v1.pdf

Code: https://github.com/fenghetan9/mambamim

https://t.me/DataScienceT ⭐️
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