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FrankTianTT
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Robot kinematics implemented in pytorch
An overview of different quaternion implementations and their chosen order: x-y-z-w or w-x-y-z?
一款轻量级、高性能、功能强大的内网穿透代理服务器。支持tcp、udp、socks5、http等几乎所有流量转发，可用来访问内网网站、本地支付接口调试、ssh访问、远程桌面，内网dns解析、内网socks5代理等等……，并带有功能强大的web管理端。a lightweight, high-performance, powerful intranet penetration proxy serv…
Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfer https://arxiv.org/abs/2404.05695
Official Implementation of the ICCV 2023 paper: Perpetual Humanoid Control for Real-time Simulated Avatars
Official Implementation of the ICLR 2024 spotlight paper: Universal Humanoid Motion Representations for Physics-Based Control
The simplest, fastest repository for training/finetuning medium-sized GPTs.
A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges
Mining technical factors based on symbolic regression via genetic algorithm
pseudocode and algorithms for the paper "Alpha$^2$: Discovering Logical Formulaic Alphas using Deep Reinforcement Learning"
Touying is a powerful package for creating presentation slides in Typst.
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
🌐 The Internet OS! Free, Open-Source, and Self-Hostable.
An open source quadruped robot pet framework for developing Boston Dynamics-style four-legged robots that are perfect for STEM, coding & robotics education, IoT robotics applications, AI-enhanced r…
Convert any binary data to a PNG image file and vice versa.
open-source feature selection repository in python
Identifiable aNd TrAnsferable Causal meTa World Model.
allRank is a framework for training learning-to-rank neural models based on PyTorch.
PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
Python Backtesting library for trading strategies
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas…
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.