MuLoCo: Muon is a practical inner optimizer for DiLoCo

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@Machine_learn

A Tutorial on Meta-Reinforcement
Learning

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@Machine_learn

COUNTING THE NUMBER OF Zp-AND Fp[t]-FIXED POINTS OF A DISCRETE DYNAMICAL
SYSTEM WITH APPLICATIONS FROM ARITHMETIC STATISTICS

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@Machine_learn

Owen 3 release

📖 Blog


@LLM_learning

Article Title:
Uncertainty Quantification for Language Models: A Suite of Black-Box, White-Box, LLM Judge, and Ensemble Scorers


PDF Download Link:
https://arxiv.org/pdf/2504.19254v2.pdf

GitHub:
• https://github.com/cvs-health/uqlm

Datasets:
• GSM8K
• SVAMP
• PopQA
@Machine_learn

Forecasting: Principles and Practice

📚 Book

@Machine_learn

Good papers



Solving Video Inverse Problems Using Image Diffusion Models



Deep Random Features for Scalable Interpolation of Spatiotemporal Data



Century: A Framework and Dataset for Evaluating Ethical Contextualisation of Sensitive Images



No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models



Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance



How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion


A Decade’s Battle on Dataset Bias: Are We There Yet?



HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models

@Machine_learn

Article Title:
s3: You Don't Need That Much Data to Train a Search Agent via RL





PDF Download Link:
https://arxiv.org/pdf/2505.14146v1.pdf

GitHub:
• https://github.com/pat-jj/s3

Datasets:
• Natural Questions
• TriviaQA
• HotpotQA
• MedQA
• PubMedQA
==================================
@Machine_learn

LINEAR ALGEBRA Jim Hefferon Fourth edition

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@Machine_learn

با عرض سلام دو موضوع رو می خواهیم به صورت گروهی ادامه بدیم.
- survey on GAN methods for time series data generation

- survey on highlights the advantages of foundation in new learning methods for time series data
این دو مقاله به صورت جلسه ای برگزار میشه و هر هفته ۱.۵ ساعت تدریس رو خواهم داشت برای کسانی که می خوان شرکت کنند. هر مقاله ۶ نفر خواهد داشت و هزینه هر نفر ۲۰۰$ خواهد بود.

دوستانی که اولین مقالشون و یا میخوان داخل این مقالات شرکت کنند به ایدی بنده مراجعه کنند.

@Raminmousa
@Machine_learn
@Paper4money

Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening

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@Machine_learn

نفرات ۲ و ۳ مربوط به GAN پر شد...!
دوستانی که تمایل دارن به بنده مراجعه کنند

@Raminmousa

Common Corpus: The Largest Collection of
Ethical Data for LLM Pre-Training

📚 Corpus

@Machine_learn

AI-agents-for-beginners

10 Lessons to Get Started Building AI Agents

Creator: Microsoft
Stars ⭐️: 16,050
Forked by: 3,926

Github Repo:
https://github.com/microsoft/ai-agents-for-beginners

@Machine_learn

Article Title:
Vision as LoRA



PDF Download Link:
https://arxiv.org/pdf/2503.20680v1.pdf

GitHub:
• https://github.com/hon-wong/vora

Datasets:
• MM-Vet
• Google Landmarks Dataset v2

@Machine_learn

An Introduction to Categorical Data Analysis Second Edition

📚 book


@Machine_learn

Article Title:
Harnessing the Universal Geometry of Embeddings

PDF Download Link:
https://arxiv.org/pdf/2505.12540v2.pdf

GitHub:
• https://github.com/rjha18/vec2vec
• https://github.com/zhaoolee/garss

Datasets:
• Natural Questions

@Machine_learn

از این مقالات تنها موضوع اول نفرات ۳ تا ۶ باقی موندن مابقی پر شدن.
دوستانی که نیاز دارن زودتر اقدام کنند.
@Raminmousa

Article Title:
MTGS: Multi-Traversal Gaussian Splatting


PDF Download Link:
https://arxiv.org/pdf/2503.12552v3.pdf

GitHub:
• https://github.com/OpenDriveLab/MTGS

Datasets:
• No datasets information available


@Machine_learn