data repository for publicly available code and data of "Low-intensity fires mitigate the risk of catastrophic wildfires in California's forests"

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

101 alpha factors calculate based on Alpha101

Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.

AmazingQuant——为交易而生的智能投研Lab。包含策略组合研究服务、量化数据服务、指标计算服务、绩效分析服务四大功能模块。

Visually explore, understand, and present your data.

😈Awful AI is a curated list to track current scary usages of AI - hoping to raise awareness

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…

Distribute and run LLMs with a single file.

Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.

An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.

Building Open-Ended Embodied Agents with Internet-Scale Knowledge

An Open-Ended Embodied Agent with Large Language Models

OpenFE: automated feature generation with expert-level performance

Official inference library for Mistral models

Performant financial charts built with HTML5 canvas

Examples of Charting Library integrations with other libraries, frameworks and data transports

Portfolio and risk analytics in Python

Zipline, a Pythonic Algorithmic Trading Library

Lean Algorithmic Trading Engine by QuantConnect (Python, C#)

current and earlier versions of PRELIM

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

Inference Llama 2 in one file of pure C

ChatGPT to Notion brings the cleverness of ChatGPT right into your Notion workspace!

A collection of AWESOME things about Graph-Related LLMs.

A topic-centric list of HQ open datasets.

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

LLM inference in C/C++