Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2 and Pytorch.
☆353Oct 17, 2024Updated last year
Alternatives and similar repositories for Deep-Learning-for-Causal-Inference
Users that are interested in Deep-Learning-for-Causal-Inference are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Must-read papers and resources related to causal inference and machine (deep) learning☆752Nov 23, 2022Updated 3 years ago
- ☆296Apr 3, 2022Updated 4 years ago
- An index of algorithms for learning causality with data☆3,266Jan 22, 2025Updated last year
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆157Jun 22, 2024Updated last year
- Counterfactual Regression☆319Dec 7, 2022Updated 3 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Uplift modeling and causal inference with machine learning algorithms☆5,841May 16, 2026Updated last week
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆26Dec 6, 2022Updated 3 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Apr 26, 2022Updated 4 years ago
- ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Inte…☆4,633Apr 27, 2026Updated 3 weeks ago
- ☆12Aug 16, 2022Updated 3 years ago
- A curated list of causal inference libraries, resources, and applications.☆1,150Apr 21, 2026Updated last month
- ☆32Apr 17, 2025Updated last year
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus …☆88Mar 29, 2021Updated 5 years ago
- Code for Conformal Counterfactual Inference under Hidden Confounding (KDD’24)☆11Aug 30, 2024Updated last year
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- Codes to replicate analysis in Baker & Gelbach (2020)☆11Apr 25, 2020Updated 6 years ago
- heterogeneous treatment effect estimation with causal forests☆12May 1, 2023Updated 3 years ago
- DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a uni…☆8,116May 17, 2026Updated last week
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆95Mar 24, 2023Updated 3 years ago
- A Python package for modular causal inference analysis and model evaluations☆816May 7, 2026Updated 2 weeks ago
- Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"☆186Aug 13, 2024Updated 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…☆19May 22, 2022Updated 4 years ago
- ☆529Dec 16, 2024Updated last year
- Curated research at the intersection of causal inference and natural language processing.☆814Feb 1, 2024Updated 2 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Code for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"☆24Apr 27, 2023Updated 3 years ago
- ☆33May 15, 2024Updated 2 years ago
- This material has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and AI …☆18May 5, 2023Updated 3 years ago
- Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure☆932Mar 16, 2026Updated 2 months ago
- Reinforcement Learning for Uplift Modeling☆13Mar 13, 2021Updated 5 years ago
- Tensorflow 2 implementation of Causal-BERT☆74Nov 5, 2023Updated 2 years ago
- Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"☆20May 28, 2023Updated 2 years ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆1,229Oct 13, 2025Updated 7 months ago
- Causal Discovery in Python. Learning causality from data.☆1,601Updated this week
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NU…☆516Mar 3, 2023Updated 3 years ago
- Code to reproduce the models and analysis in the paper "Leveraging the Alignment between Machine Learning and Intersectionality: Using W…☆17Mar 19, 2021Updated 5 years ago
- A data index for learning causality.☆491Oct 25, 2023Updated 2 years ago
- DoubleML - Double Machine Learning in Python☆738May 13, 2026Updated last week
- Resources to learn more about Machine Learning and Artificial Intelligence☆30Jun 3, 2021Updated 4 years ago
- Code accompanying the paper "Empirical analysis of model selection for heterogeneous causal effect estimation"☆17Jan 28, 2025Updated last year
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆78Jul 8, 2021Updated 4 years ago