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 2 months ago
- Implementation of paper DESCN, which is accepted in SIGKDD 2022.☆97Updated last year
- mtgbmcode☆174Updated 3 years ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆17Updated 6 years ago
- Build a python version causal inference model for Pcalg☆19Updated 5 years ago
- code for "Addressing Exposure Bias in Uplift Modeling forLarge-scale Online Advertising"☆35Updated 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】☆145Updated 2 years ago
- pytorch implementation of dragonnet☆44Updated 2 years ago
- Experiments codes for SIGKDD '23 paper "Explicit Feature Interaction-aware Uplift Network for Online Marketing"☆74Updated last year
- The real-world Production Dataset from E-commerce platform Meituan☆28Updated last year
- 因果推理&AB实验相关论文小书库☆238Updated 2 years ago
- ☆279Updated 3 years ago
- ☆21Updated 3 years ago
- ☆34Updated 3 years ago
- PAKDD AutoML challenge 2nd Feature Engineering Part☆71Updated 4 years ago
- 利用lightgbm做(learning to rank)排序学习，包括数据处理、模型训练、模型决策可视化、模型可解释性以及预测等。Use LightGBM to learn ranking, including data processing, model trainin…☆270Updated 2 years ago
- [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…☆86Updated 2 years ago
- Rankability Enhanced Revenue Uplift Modeling Framework for Online Marketing (KDD 2024)☆14Updated last year
- Implement PC algorithm in Python | PC 算法的 Python 实现☆118Updated last year
- Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing (KDD 2024)☆28Updated last year
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆65Updated last year
- OpenASCE (Open All-Scale Casual Engine) is a Python package for end-to-end large-scale causal learning. It provides causal discovery, cau…☆77Updated last year
- Pytorch implementation of Adaptive Information Transfer Multi-task (AITM)☆18Updated 3 years ago
- 第三届 Apache Flink 极客挑战赛暨AAIG CUP——电商推荐“抱大腿”攻击识别亚军代码方案☆29Updated 3 years ago
- 一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM, xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... （pytorch, tf2.0）☆269Updated 3 months ago
- I have surveyed the technology and papers of CTR & Recommender System, and implemented 25 common-used models with Pytorch for reusage. …☆53Updated last year
- Reproducing Shalit et al.'s Individual Treatment Effect model. This is a deep neural net that can be applied to various problems in causa…☆18Updated 3 years ago
- esmm model by tensorflow keras☆70Updated 4 years ago
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆69Updated 4 months ago