xy-zheng

xy-zheng's Stars

• ashishpatel26/LLM-Finetuning

  LLM Finetuning with peft

  Language:Jupyter Notebook2.1k580

• jd-opensource/UTBoost

  A powerful tree-based uplift modeling system.

  Language:C++262

• Kyushik/Generative-Model

  Repository for implementation of generative models with Tensorflow 1.x

  Language:Jupyter Notebook718

• hwalsuklee/tensorflow-generative-model-collections

  Collection of generative models in Tensorflow

  Language:Python3.9k859

• WeijiaZhang24/TEDVAE

  Code for TEDVAE, a VAE-based treatment effect estimation algorithm.

  Language:Python199

• uber/causalml

  Uplift modeling and causal inference with machine learning algorithms

  Language:Python5k770

• 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.

  Language:Jupyter Notebook3.8k713

• anpwu/DeR-CFR

  Language:Python174

• Osier-Yi/SITE

  Language:Python5510

• xy-zheng/Segmented-Linear-Regression-Tree

  Language:Python91

• wubotong/LaCIM

  Language:Python233

• dsgiitr/d2l-pytorch

  This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.

  Language:Jupyter Notebook4.2k1.2k

• caus-am/jci

  Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)

  Language:R143

• yfzhang114/Generalization-Causality

  关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

  1.2k103

• jemolano1498/Reproducibility_project_CS4240

  Language:Python1

• clinicalml/cfrnet

  Counterfactual Regression

  Language:Python29382

• KunKuang/Differentiated-Confounder-Balancing

  The source code of our DCB algorithm in KDD17 paper: Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing

  Language:Matlab10

• mrojascarulla/causal_transfer_learning

  Language:Python307

• caus-am/dom_adapt

  Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"

  Language:R184

• Biwei-Huang/Causal-Discovery-from-Nonstationary-Heterogeneous-Data

  Causal Discovery from Nonstationary/Heterogeneous Data.

  Language:MATLAB506

• mgong2/DA_Infer

  Domain Adaptation as a Problem of Inference on Graphical Models

  Language:Python293

• AMLab-Amsterdam/DIVA

  Implementation of 'DIVA: Domain Invariant Variational Autoencoders'

  Language:Python9819

• FlyHighest/UnrealPerson

  [CVPR-2021] UnrealPerson: An adaptive pipeline for costless person re-identification

  Language:Python748

• AMLab-Amsterdam/DataAugmentationInterventions

  Language:Python273

• Bruuuuuuce/PKUAutoSubmit

  PKU一键出入校备案小工具

  Language:Python177272

• pytorch/vision

  Datasets, Transforms and Models specific to Computer Vision

  Language:Python16.1k6.9k

• FlyHighest/Single-Camera-Training-ReID

  Codes and datasets of AAAI 2020 paper: Single camera training for person re-identification

  Language:Python236