Popular GitHub Repositories for Resampling Methods

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

? LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

A curated list of awesome self-supervised methods

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

A collection of important graph embedding, classification and representation learning papers with implementations.

Probabilistic reasoning and statistical analysis in TensorFlow

Text recognition (optical character recognition) with deep learning methods, ICCV 2019

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！

Learning in infinite dimension with neural operators.

A curated list of resources for text detection/recognition (optical character recognition ) with deep learning methods.

Chess reinforcement learning by AlphaGo Zero methods.

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

? An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

TensorLy: Tensor Learning in Python.

A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. ?25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. ? Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.