🤗 Evaluate: A library for easily evaluating machine learning models and datasets.

pix2tex: Using a ViT to convert images of equations into LaTeX code.

[CVPR'24 Oral] Mip-Splatting: Alias-free 3D Gaussian Splatting

[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

This repository accompanies our research entitled "Using Monocular Depth Estimation for Distance Estimation in a Moving Vehicle," which introduces a method of actualizing generated monocular depth …

Easy NeRF synthetic dataset creation within Blender

一本系统地教你将深度学习模型的性能最大化的战术手册。

Latent Text-to-Image Diffusion

Stable Diffusion web UI

深度学习经典、新论文逐段精读

《数学要素》，583幅图，136个代码文件，其中24个Streamlit App；状态：清华社五审五校中；Github稿件基本稳定，欢迎提意见，会及时修改

https://hrl.boyuai.com/

《矩阵力量》，584幅图，81个代码文件，其中18个Streamlit App；状态：清华社五审五校中；Github稿件基本稳定，欢迎提意见，会及时修改

A standard API for reinforcement learning and a diverse set of reference environments (formerly Gym)

📚 Freely available programming books

本文原文由知名 Hacker Eric S. Raymond 所撰寫，教你如何正確的提出技術問題並獲得你滿意的答案。

DevOps Guide - Development to Production all configurations with basic notes to debug efficiently.

Master the command line, in one page

Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)

Code Repository for The Kaggle Book, Published by Packt Publishing

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

计算机自学指南

the resources I use to learn computer science in my spare time

The interactive graphing library for Python (includes Plotly Express) ✨

Graph Neural Network Library for PyTorch

It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced research…

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

KDD 2019: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

Object detection and instance segmentation toolkit based on PaddlePaddle.

Implementation of MTAD-GAT: Multivariate Time-series Anomaly Detection via Graph Attention Network