liangoy / WAIC2022CausalLinks
☆10Updated 2 years ago
Alternatives and similar repositories for WAIC2022Causal
Users that are interested in WAIC2022Causal are comparing it to the libraries listed below
Sorting:
- ☆40Updated 4 years ago
- YLearn, a pun of "learn why", is a python package for causal inference☆429Updated 4 months ago
- Implementation of paper DESCN, which is accepted in SIGKDD 2022.☆98Updated last year
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆17Updated 6 years ago
- 因果推理&AB实验相关论文小书库☆241Updated 2 years ago
- mtgbmcode☆176Updated 3 years ago
- [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…☆90Updated 3 years ago
- Build a python version causal inference model for Pcalg☆19Updated 6 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】☆149Updated 2 years ago
- ☆285Updated 3 years ago
- EconML/CausalML KDD 2021 Tutorial☆163Updated 2 years ago
- code for "Addressing Exposure Bias in Uplift Modeling forLarge-scale Online Advertising"☆36Updated 3 years ago
- OpenASCE (Open All-Scale Casual Engine) is a Python package for end-to-end large-scale causal learning. It provides causal discovery, cau…☆80Updated last year
- ☆22Updated 3 weeks ago
- A powerful tree-based uplift modeling system.☆32Updated last year
- ☆32Updated last month
- Causal Effect Engine is a Golang package for causal inference☆18Updated 3 years ago
- pytorch implementation of dragonnet☆45Updated 3 years ago
- ☆34Updated 3 years ago
- Counterfactual Regression☆25Updated 9 years ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆67Updated last year
- Experiments codes for SIGKDD '23 paper "Explicit Feature Interaction-aware Uplift Network for Online Marketing"☆81Updated last year
- ☆25Updated 6 years ago
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆72Updated 6 months ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆91Updated 2 years ago
- Rankability Enhanced Revenue Uplift Modeling Framework for Online Marketing (KDD 2024)☆17Updated last year
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆150Updated last year
- The real-world Production Dataset from E-commerce platform Meituan☆30Updated last year
- This project is a research on how to extract rules from the existing data using trained Decision Tree. The dataset used to train the mode…☆16Updated 6 years ago
- ☆59Updated 3 years ago