MinaGhadimiAtigh

MinaGhadimiAtigh's Stars

• microsoft/ML-For-Beginners

  12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

  Language:HTML69.9k1k13614.6k

• microsoft/generative-ai-for-beginners

  21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

  Language:Jupyter Notebook65.4k56012933.5k

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook47.9k3086755.7k

• microsoft/AI-For-Beginners

  12 Weeks, 24 Lessons, AI for All!

  Language:Jupyter Notebook35k4101145.9k

• google-research/tuning_playbook

  A playbook for systematically maximizing the performance of deep learning models.

  27.4k286422.3k

• BradyFU/Awesome-Multimodal-Large-Language-Models

  :sparkles::sparkles:Latest Advances on Multimodal Large Language Models

  12.8k274121822

• pytorch-labs/gpt-fast

  Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.

  Language:Python5.7k60104514

• lucidrains/x-transformers

  A concise but complete full-attention transformer with a set of promising experimental features from various papers

  Language:Python4.8k56230419

• turboderp/exllamav2

  A fast inference library for running LLMs locally on modern consumer-class GPUs

  Language:Python3.7k35462283

• VladimirYugay/Gaussian-SLAM

  Gaussian-SLAM: Photo-realistic Dense SLAM with Gaussian Splatting

  Language:Python935553959

• yhLeeee/Awesome-LLMs-in-Graph-tasks

  A curated collection of research papers exploring the utilization of LLMs for graph-related tasks.

  5368551

• dongzhuoyao/awesome-flow-matching

  A summary of related works about flow matching, stochastic interpolants

  33914212

• AvivBick/awesome-ssm-ml

  Reading list for research topics in state-space models

  24213025

• CompVis/image2video-synthesis-using-cINNs

  Implementation of Stochastic Image-to-Video Synthesis using cINNs.

  Language:Python18413830

• xiaoiker/Awesome-Hyperbolic-NeuralNetworks

  Papers and Codes for the deep learning in hyperbolic space

  17110115

• maxvanspengler/hyperbolic_learning_library

  An extension of the PyTorch library containing various tools for performing deep learning in hyperbolic space.

  Language:Python1375189

• akshitac8/tfvaegan

  [ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL

  Language:Python12953331

• dalab/hyperbolic_cones

  Source code for the ICML'18 paper "Hyperbolic Entailment Cones for Learning Hierarchical Embeddings", https://arxiv.org/abs/1804.01882

  Language:Python12914111

• SarahRastegar/Best-Papers-Top-Venues

  Best Papers of Top Venues like CVPR, NeurIPS, ICLR, ICML, ICCV, ECCV, ...

  75305

• kaytu-io/pennywise

  Be wise with your Pennies. Estimate the cost of your cloud Infrastructure before deployment.

  Language:Go63401

• wenjiaXu/VGSE

  Language:Python37571

• CompVis/behavior-driven-video-synthesis

  Language:Python27908

• ethanlshen/HierNet

  Code for "Are “Hierarchical” Visual Representations Hierarchical?" in NeurIPS Workshop for Symmetry and Geometry in Neural Representations.

  Language:Jupyter Notebook19101

• SarahRastegar/Open-World-Papers

  A comprehensive collection of open world papers from top tier conferences and journals

  17101

• msmathcomp/hyperbolic-tsne

  Experiments and content for the "Accelerating hyperbolic t-SNE" paper.

  Language:Python112257