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
HeinerKremer/sinkhorn-iv
Code for the Sinkhorn Method of Moments estimator for instrumental variable regression
xinychen/awesome-latex-drawing
Drawing Bayesian networks, graphical models, tensors, technical frameworks, and illustrations in LaTeX.
xinychen/academic-drawing
Providing codes (including Matlab and Python) for visualizing numerical experiment results.
xinychen/tensor-book
张量计算系列教程 (Tensor Computations Tutorials)
tangxiangru/awesome-causal-inference
Reading list for research topics in causal inference.
simeon-spasov/RandomCausalGraphs
A library for simulating random causal graphs.
mkchenxi/Causal-Inference
Causal Inference Course at St. Gallen
jasonamilne/causality
This repository aims to provide a comprehensive collection of methods for performing causal inference, including experimental designs, statistical methods, and advanced machine learning techniques. Each method will be implemented and documented with examples.
chaix026/Causal-Inference
Causal inference methods
shreyap18/cddr_bivariate
All code, results and images for the CDDR bivariate paper
Vincent-wq/causal_course_eeg
The course materials for ohbm 2024 educational courses Global Open Science Electrophysiology-Causal inference in clinical neuroscience with open science EEG.
dscolby/CausalELM.jl
Taking causal inference to the extreme!
deshen24/syntheticNN
tmichoel/causal-inference-short-course
Lecture material for a short course on causal inference in drug discovery
WeiHuang05/Awesome-Feature-Learning-in-Deep-Learning-Thoery
Welcome to the Awesome Feature Learning in Deep Learning Thoery Reading Group! This repository serves as a collaborative platform for scholars, enthusiasts, and anyone interested in delving into the fascinating world of feature learning within deep learning theory.
scunning1975/advanced_causalinf
Advanced causal inference and research design course
amnudn/statelearner
borusyak/are213
PhD Applied Econometrics class taught at UC Berkeley
haotiansun14/SpecIV
Spectral Representation for Causal Estimation with Hidden Confounders
victor5as/mr_causal_attribution
Multiply-Robust Causal Change Attribution
jinshi201/Proxy_variable
Automating the Selection of Proxy Variables of Unmeasured Confounders
r-causal/causal_inference_r_workshop
Causal Inference in R Workshop
danieletramontano/Causal-Effect-Identification-in-LiNGAM-Models-with-Latent-Confounders
gloewing/causal_opto
Causal Inference in the Closed Loop
DanielaSchkoda/TestLinearSEM
jaydu1/CausalMultiOutcomes
Causal Inference for Genomic Data with Multiple Heterogeneous Outcomes
konstantingoe/causal_reading
xuzhiqin1990/understanding_dl
A lecture note for understanding deep learning
cwolock/survML
Tools for Flexible Survival Analysis Using Machine Learning
ilundberg/teaching
Teaching materials