Book: 📚Introduction to Generative AI
Authors: Numa Dhamani and Maggie Engler
ISBN: Null
year: 2023
pages: 318
Tags: #AI
@Machine_learn

Graph Diffusion Policy Optimization

🖥 Github: https://github.com/sail-sg/gdpo

📕 Paper: https://arxiv.org/pdf/2402.16302v1.pdf

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

✨ Tasks: https://paperswithcode.com/task/graph-generation

@Machine_learn

DCVSMNet: Double Cost Volume Stereo Matching Network

🖥 Github: https://github.com/m2219/dcvsmnet

📕 Paper: https://arxiv.org/pdf/2402.16473v1.pdf

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

✨ Tasks: https://paperswithcode.com/task/stereo-matching-1

@Machine_learn

Book: 📚Fundamentals of Data Science Theory and Practice
Authors: Jugal K. Kalita Dhruba K. Bhattacharyya Swarup Roy
ISBN: 978-0-323-91778-0
year: 2023
pages: 336
Tags: #Data_science
@Machine_learn

با عرض سلام
مقاله ي فوق به صورت كامل نوشته شده است. نيازمند شخصي هستيم كه بتونه اكسپت مقاله رو بگيره و هزينه هاي سرور رو پرداخت كنه(جايگاه ٢: co-author).

@Raminmousa

ZHEM: An Integrated Data Processing Framework for Pretraining Foundation Models

🖥 Github: https://github.com/emanual20/zhem

📕 Paper: https://arxiv.org/pdf/2402.16358v1.pdf

🔥Dataset: https://paperswithcode.com/dataset/wikitext-2

@Machine_learn

🖼 Differential Diffusion: Giving Each Pixel Its Strength 🔥

▪code: github.com/exx8/differential-diffusion
▪page: differential-diffusion.github.io
▪paper: arxiv.org/abs/2306.00950

@Machine_learn

Book: 📚Python code for Artificial Intelligence Foundations of Computational Agents
Authors: David L. Poole and Alan K. Mackworth
year: 2024
pages: 392
Tags: #Python
@Machine_learn

⚡️ ResAdapter: Domain Consistent Resolution Adapter for Diffusion Models

▪page: https://res-adapter.github.io
▪paper: https://arxiv.org/abs/2403.02084
▪code: https://github.com/bytedance/res-adapter

@Machine_learn

VTG-GPT

🖥 Github: https://github.com/YoucanBaby/VTG-GPT

📕 Paper: https://arxiv.org/pdf/2403.02076v1.pdf

🔥Dataset: https://paperswithcode.com/dataset/activitynet-captions

✨ Tasks: https://paperswithcode.com/task/zero-shot-moment-retrieval

@Machine_learn

Book: 📚Exercises in Machine Learning
Authors: Michael U. Gutmann
year: 2024
pages: 211
Tags: #ML
@Machine_learn

Arbitrary-Scale Point Cloud Upsampling by Voxel-Based Network with Latent Geometric-Consistent Learning

🖥 Github: https://github.com/hikvision-research/3dvision

📕 Paper: https://arxiv.org/abs/2403.05117v1

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

@Machine_learn

Book: 📚grokking Deep Reinforcement Learning
Authors: Miguel Morales Foreword by Charles Isbell, Jr.
year: 2020
pages: 472
Tags: #RL #DRL
@Machine_learn

رمضان الکریم


توبوا إلى الله توبة نصوحا
@Machine_learn

ViT-CoMer: Vision Transformer with Convolutional Multi-scale Feature Interaction for Dense Predictions

🖥 Github: https://github.com/Traffic-X/ViT-CoMer

📕 Paper: https://arxiv.org/pdf/2403.07392.pdf

✨ Tasks: https://paperswithcode.com/task/object-detection

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

@Machine_learn