zikunye2 / deep_learning_based_causal_inference_for_combinatorial_experimentsLinks
codes for the paper Deep Learning Based Casual Inference for Combinatorial Experiments
☆11Updated 2 months ago
Alternatives and similar repositories for deep_learning_based_causal_inference_for_combinatorial_experiments
Users that are interested in deep_learning_based_causal_inference_for_combinatorial_experiments are comparing it to the libraries listed below
Sorting:
- Implementation of "Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework" (JASA 2023)☆30Updated last year
- Code for the paper "Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies".☆18Updated last year
- Code for Colangelo and Lee (2025)☆14Updated 4 months ago
- Software package for intertemporal pricing optimization under reference effects and consumer heterogeneity estimation. Please see REAMDE.…☆10Updated last year
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆75Updated 3 years ago
- Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"☆17Updated 2 years ago
- Causality with machine learning, topic including causal represenation learning, causal reinforcement learning☆11Updated 4 years ago
- An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…☆14Updated 11 months ago
- Data-Driven operations management - https://d3group.github.io/ddop☆16Updated last year
- Replication Code for Paper "Stochastic Optimization Forests".☆20Updated 3 years ago
- ☆33Updated 2 weeks ago
- Datasets for Causal-Structure-Learning Repo☆15Updated 5 years ago
- ☆8Updated 2 years ago
- ☆10Updated 3 years ago
- Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensig…☆21Updated 3 years ago
- ☆34Updated 2 years ago
- ☆22Updated last week
- ☆24Updated 3 years ago
- Reproducing Shalit et al.'s Individual Treatment Effect model. This is a deep neural net that can be applied to various problems in causa…☆17Updated 3 years ago
- Package for building Market Segmentation Trees, Choice Model Trees, and Isotonic Regression Trees☆17Updated 2 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆83Updated 7 years ago
- ☆35Updated 5 years ago
- Open source implementation of sDTM - supervised Deep Topic Model☆16Updated 3 years ago
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆49Updated 6 years ago
- ☆39Updated 6 years ago
- Method based on neural networks and variational inference for causal discovery under latent interventions, i. e. learning a shared causal…☆19Updated 3 years ago
- ☆9Updated last year
- ☆9Updated last year
- ☆23Updated 3 years ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆63Updated last year