70 skills found · Page 1 of 3
py-why / EconMLALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
pgmpy / PgmpyPython Toolkit for Causal and Probabilistic Reasoning
KaihuaTang / Long Tailed Recognition.pytorch[NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation (LVIS). It is also a PyTorch implementation of the NeurIPS 2020 paper 'Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect'.
AMLab-Amsterdam / CEVAECausal Effect Inference with Deep Latent-Variable Models
vdblm / CausalPFNCausalPFN: Amortized Causal Effect Estimation via In-Context Learning
Open-All-Scale-Causal-Engine / OpenASCEOpenASCE (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.
JeanKaddour / SINCausal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
Hazrat-Ali9 / Interpretable Spatio Temporal GNNs For Causal Effects Of NO On Schoolchildren S Respiratory Health✈ Interpretable 🚁 Spatio 🚀 Temporal 🛬 GNNs 🕌 Causal 🚢 Effects of 🛸 NO 🏡 on 🚋 Schoolchildren’s 🚂 Health is a 🛩 cutting edge 🚞 research 🚄 that leverages 🛳 Graph ⛴ Neural Networks 🚟 Causal 🚠 Inference to 🚋 analyze ⚽ Nitrogen ⚾ Oxide (NO₂) 🥎 exposure 🏀 affects the 🏐 respiratory 🏈 health of 🎮 schoolchildren 🧶 over 🎁 space 🏩time
kaz-yos / RegmedintR implementation of effect measure modification-extended regression-based closed-formula causal mediation analysis
J-FHu / CEMCodes of Interpreting Low-level Vision Models with Causal Effect Maps
Bodhi8 / PycausalsimPyCausalSim is a Python framework for discovering and validating causal relationships through simulation. Unlike traditional analytics that only show correlation, PyCausalSim uses counterfactual simulation and structural causal models to identify true cause-and-effect relationships in your data.
yqzhong7 / AIPWR Package: Augmented Inverse Probability Weighted (AIPW) Estimation for Average Causal Effect
anthem-ai / BcaussCode for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"
anndvision / QuinceCode for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
zzz47zzz / CFNER[EMNLP2022] Released code for paper "Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition"
aaronwtr / Cfrnet ReproductionReproducing Shalit et al.'s Individual Treatment Effect model. This is a deep neural net that can be applied to various problems in causal inference.
L-F-Z / CEECausal Effect Engine is a Golang package for causal inference
dalmiral / MHealthModerationSimulation results for "Assessing Time-Varying Causal Effect Moderation in Mobile Health"
amit-sharma / Splitdoor Causal CriterionA method for estimating causal effects in time-series data. Uses available data to automatically find natural experiments for identifying causal effect.
zhaoshitian / Causal CoG[CVPR'24 Highlight] Implementation of "Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models"
