yezichu
I am currently studying at Fudan University ISTBI, with a research focus on causal inference and machine learning theory.
Fudan UniversityShanghai
yezichu's Stars
getkeops/keops
KErnel OPerationS, on CPUs and GPUs, with autodiff and without memory overflows
cdt15/lingam
Python package for causal discovery based on LiNGAM.
shaodaqian/DML-IV
Implementation of Learning Decision Policies with Instrumental Variables through Double Machine Learning
RunzheStat/TestMDP
Implementation of "Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making”(ICML 2020) in Python
kyunghyuncho/2024-causal-inference-machine-learning
jennalandy/interference-review
A review of causal inference approaches with partial interference
stanford-policylab/causal-fairness
Causal Conceptions of Fairness and their Consequences
peppermin-t/ml-notes
Notes on machine learning topics, including machine learning & pattern recognition, probabilistic modelling and reasoning, and causal inference.
kolesarm/539b
(Advanced) Applied Econometrics
alejandroh3005/causal-inference
Course repository for BIOST 578: Causal Inference for Biomedical Studies (Spring 2024) with Dr. Ting Ye
syanga/hidmed
Causal Inference with Hidden Mediators
tlverse/hal-workshops
Teaching materials for HAL workshops and short courses
kevjosey/causal-me
Causal Inference with a Continuous Error-Prone Exposure
ssejal/causal-inference
Learning and exploration through causal inference topics
LQ-sama/Causal_ML_For_EEG
Diagnosis and Causal Analysis of Depression Based on EEG Features and Machine Learning: 对EEG脑电信号与抑郁症关系的因果分析
dylanskinner65/CausalInference
Project for Math 522 at BYU. We are interested in understanding causal inference in deep learning.
y0-causal-inference/eliater
A high level, end-to-end causal inference workflow
dcacciarelli/my-causality-book
yuchen-zhu/mekiv
FlavScheidt/causalGossipSub
Causal Discovery and Analysis of GossipSub over the XRP Ledger
CausalInference/pygformula
The pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-varying treatments and confounders to estimate the risk or mean of an outcome under hypothetical treatment strategies specified by the user.
TianyiPeng/causaltensor
A python package for causal inference in panels
IPL-UV/confound_it
jmetzen/kernel_regression
Implementation of Nadaraya-Watson kernel regression with automatic bandwidth selection compatible with sklearn.
Jakefawkes/DR_distributional_test
This repo contains the code for the paper "Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects"
owmork/causal_data_science
Lab Sessions - Causal Data Science for Business Analytics (Summer Term 2024)
sb-ai-lab/HypEx
Fast and customizable framework for automatic and quick Causal Inference in Python
gsrubio/causality-and-experimentation
Portfolio projects on Data Analysis, Data Visualization and Machine Learning
harrya32/STEAM
SUwonglab/CausalEGM
A General Causal Inference Framework by Encoding Generative Modeling