statsqixu's Stars
YaohuiZeng/grpregOverlap
Regularization paths of linear, logistic, Poisson, or Cox models with overlapping grouped covariates
aangelopoulos/ppi_py
A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.
seandavi/awesome-single-cell
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
lotten/uci-thesis-latex
LaTeX template for thesis and dissertation documents at UC Irvine
kw2934/ARMUL
Adaptive and Robust Multi-Task Learning
statsqixu/DEM
Double Encoder Model (DEM): An indirect approach to estimate Individualized Treatment Rule (ITR) for Combination Treatment
statsqixu/MLRWL
Multi-Label Residual Weighted Learning (MLRWL) for individualized combination treatment rule
py-why/EconML
ALICE (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.
unlearning-challenge/starting-kit
Starting kit for the NeurIPS 2023 unlearning challenge
ctlllll/reward_collapse
kimmo1019/Roundtrip
Roundtrip: density estimation with deep generative neural networks
liuhh02/game-theory-coursera
Lecture Slides, Notes and Problem Set Answers to the Game Theory course on Coursera by Stanford University and The University of British Columbia
SupeRuier/awesome-active-learning
Everything you need about Active Learning (AL).
orchidproject/active-crowd-toolkit
ActiveCrowdToolkit: Benchmarking tools for crowdsourcing research
JoKerDii/bspline-PyTorch-blocks
A customized PyTorch layer and a customized PyTorch activation function using B-spline transformation
patrick-kidger/torchcubicspline
Interpolating natural cubic splines. Includes batching, GPU support, support for missing values, evaluating derivatives of the spline, and backpropagation.
Billy1900/Awesome-Differential-Privacy
Differential private machine learning
google-research/disentanglement_lib
disentanglement_lib is an open-source library for research on learning disentangled representations.
sootlasten/disentangled-representation-papers
A curated list of research papers related to learning disentangled representations
SCXsunchenxi/ISMTS-Review
wangshusen/DeepLearning
TrentoCrowdAI/crowdsourced-datasets
Crowdsourced datasets including the individual crowd votes.
Ma-Lab-Berkeley/ReduNet
ReduNet
HIPS/autograd
Efficiently computes derivatives of NumPy code.
pymanopt/pymanopt
Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation
lezcano/geotorch
Constrained optimization toolkit for PyTorch
sherpa-ai/sherpa
Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
Aura-healthcare/hrv-analysis
Package for Heart Rate Variability analysis in Python
fuhaoda/ITR
cvxgrp/dccp
A CVXPY extension for convex-concave programming