Open-All-Scale-Causal-Engine / OpenASCE
OpenASCE (Open All-Scale Casual Engine) is a Python package for end-to-end large-scale causal learning. It provides causal discovery, causal effect estimation and attribution algorithms all in one package.
☆70Updated last year
Alternatives and similar repositories for OpenASCE:
Users that are interested in OpenASCE are comparing it to the libraries listed below
- YLearn, a pun of "learn why", is a python package for causal inference☆410Updated 5 months ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆15Updated 5 years ago
- It is a high-performance causal inference (statistical model) computing library based on OLAP, which solves the performance bottleneck of…☆131Updated 2 months ago
- CausalMatch is a Bytedance research project aimed at integrating cutting-edge machine learning and econometrics methods to bring about au…☆49Updated last month
- Ant Graph Learning (AGL) provides a comprehensive solution for graph learning tasks at an industrial scale.☆84Updated last year
- 因果推理&AB实验相关论文小书库☆219Updated last year
- ☆39Updated 3 years ago
- 🛠 How to Apply Causal ML to Real Scene Modeling？How to learn Causal ML？【✔从Causal ML到实际场景的Uplift建模】☆123Updated last year
- Implementation of paper DESCN, which is accepted in SIGKDD 2022.☆74Updated last year
- ☆105Updated last year
- ☆18Updated 3 years ago
- ☆10Updated last year
- 在常规推荐系统算法和系统双优化的范式下，一线公司针对单个任务或单个业务的效果挖掘几乎达到极限。从2019年我们开始关注多种信息的萃取融合，提出了OneRec算法，希望通过平台或外部各种各样的信息来进行知识集成，打破数据孤岛，极大扩充推荐的“Extra World Knowl…☆106Updated last month
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆74Updated 3 years ago
- Source code of AAAI'22 paper: A Hybrid Causal Structure Learning Algorithm for Mixed-type Data☆38Updated 2 years ago
- ☆34Updated last year
- ☆58Updated 2 years ago
- [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…☆72Updated 2 years ago
- ☆33Updated 3 years ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆62Updated 11 months ago
- Implement PC algorithm in Python | PC 算法的 Python 实现☆117Updated last year
- 把因果思维融入机器学习中☆79Updated 5 years ago
- Causality with machine learning, topic including causal represenation learning, causal reinforcement learning☆11Updated 3 years ago
- An example project for training a GraphSAGE Model, and setup a Real-time Fraud Detection Web Service(Frontend and Backend) with NebulaGra…☆33Updated 2 years ago
- Build a python version causal inference model for Pcalg☆19Updated 5 years ago
- Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"☆15Updated last year
- Implementation of the paper: WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engin…☆83Updated 10 months ago
- Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing (KDD 2024)☆23Updated 8 months ago
- Implementation of RiskLoc, a method for localizing multi-dimensional root causes.☆125Updated 4 months ago
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆66Updated 6 months ago