Trending AI reposUpdated daily from GitHub

Basic Utilities for PyTorch Natural Language Processing (NLP)

The official repo for [NeurIPS'22] "ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation" and [TPAMI'23] "ViTPose++: Vision Transformer for Generic Body Pose Estimation"

A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow

Official repository of the xLSTM.

A high-level machine learning and deep learning library for the PHP language.

A pytorch CUDA extension implementation of instant-ngp (sdf and nerf), with a GUI.

🦁 Lion, new optimizer discovered by Google Brain using genetic algorithms that is purportedly better than Adam(w), in Pytorch

The AI Compendium, previously called the ML Compendium, curates resources and explanations of machine learning (ML) and deep learning, from a business problem through data, AI, engineering, and product.

Machine learning on FPGAs using HLS

Pytorch implementation of RetinaNet object detection.

Jupyter notebooks for using & learning Keras

开源社区第一个能下载、能运行的中文 LLaMA2 模型！

Reformer, the efficient Transformer, in Pytorch

Handwritten Text Recognition (HTR) system implemented with TensorFlow.

EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit

PyTorch implementation of adversarial attacks [torchattacks]

SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.

OpenMMLab Rotated Object Detection Toolbox and Benchmark

Master Federated Learning in 2 Hours—Run It on Your PC!

JAX - A curated list of resources https://github.com/google/jax

Corridor Key 2.0 for all your green and blue screen needs

Text to image synthesis using thought vectors

nannyml: post-deployment data science in python

Convert images of LaTex math equations into LaTex code.

A sketch extractor for anime/illustration.

Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

Repository containing notebooks of my posts on Medium

C++ Implementation of PyTorch Tutorials for Everyone

This is originally a collection of papers on neural network accelerators. Now it's more like my selection of research on deep learning and computer architecture.

PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

A toolkit for reproducible reinforcement learning research.

DIAMOND (DIffusion As a Model Of eNvironment Dreams) is a reinforcement learning agent trained in a diffusion world model. NeurIPS 2024 Spotlight.

Wifi & BLE driven passenger flow metering with cheap ESP32 boards

A Unified Framework for Surface Reconstruction

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

开源人脸口罩检测模型和数据 Detect faces and determine whether people are wearing mask.

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Avalanche: an End-to-End Library for Continual Learning based on PyTorch.

MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.

Robust realtime face and facial landmark tracking on CPU with Unity integration

Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)

Reinforcement Learning environments based on the 1993 game Doom :godmode:

Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)

Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).

Implementation of EfficientNet model. Keras and TensorFlow Keras.

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

Benchmark datasets, data loaders, and evaluators for graph machine learning

Deep and online learning with spiking neural networks in Python

Audio generation using diffusion models, in PyTorch.

A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values