mayii2001

mayii2001's Stars

• vanderschaarlab/DECAF

  DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks

  Language:Python2111

• 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 Notebook4.3k769

• jil095/tinyRNN

  Language:Python2515

• dandls/moc

  Multi-Objective Counterfactuals

  Language:R4213

• thefirebanks/Blood-Pressure-Simulator

  Replication of the paper by Myers et. al (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5487539/) with python and sagemath. Modelling blood pressure using a compartment model and ordinary differential equations

  Language:Jupyter Notebook1

• lcastri/causalflow

  CausalFlow: a Unified Framework for Causality in Time-Series

  Language:Python595

• ckassaad/causal_discovery_for_time_series

  Causal discovery for time series

  Language:Jupyter Notebook10024

• sjblim/rmsn_nips_2018

  Language:Python408

• Dhawgupta/choudhary2024icu

  Repository which contains implementation of baselines algorithms including PPO, DQN and SAC for the ICU Sepsis benchmark (https://github.com/icu-sepsis/icu-sepsis), introduced in "ICU-Sepsis: A Benchmark MDP Built from Real Medical Data", accepted in RLC 2024.

  Language:Python3

• icu-sepsis/icu-sepsis

  ICU-Sepsis is a lightweight, yet challenging RL environment that models the treatment of sepsis in the ICU.

  Language:Python27

• aniruddhraghu/sepsisrl

  Reinforcement Learning for optimal sepsis treatment policies

  Language:Jupyter Notebook10454

• florisdenhengst/guideline-informed-vent-rl

  Guideline-informed reinforcement learning for mechanical ventilation in critical care

  Language:Jupyter Notebook21

• Healthy-AI/IncomeSCM

  Language:Python6

• opendilab/DI-engine-docs

  DI-engine docs (Chinese and English)

  Language:Python30864

• xwshen51/DEAR

  Disentangled gEnerative cAusal Representation (DEAR)

  Language:Python619

• jingyaogong/minimind

  🚀🚀 「大模型」2小时完全从0训练26M的小参数GPT！🌏 Train a 26M-parameter GPT from scratch in just 2h!

  Language:Python26.2k3.1k

• amin-nejad/mimic-text-generation

  Master's project

  Language:Jupyter Notebook197

• zhendong3wang/counterfactuals-for-event-sequences

  Style-transfer Counterfactual Explanations: An Application to Mortality Prevention of ICU Patients (Artificial Intelligence in Medicine journal)

  Language:Jupyter Notebook31

• USM-CHU-FGuyon/BlendedICU

  OMOP standardization pipeline for ICU databases

  Language:Python4419

• som-shahlab/ehrshot-benchmark

  A benchmark for few-shot evaluation of foundation models for electronic health records (EHRs)

  Language:Jupyter Notebook19124

• seedatnabeel/TE-CDE

  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)

  Language:Python279

• rlditr23/RL-DITR

  Language:Python2510

• yanchao0222/tutorial_data_synthesis_and_evaluation

  Language:Jupyter Notebook4

• MuhangTian/TimeDiff

  Code to generate realistic synthetic healthcare data with diffusion models

  Language:Jupyter Notebook226

• nhsx/SynthVAE

  Synthetic data generation by a Variational AutoEncoder with Differential Privacy assessed using Synthetic Data Vault metrics

  Language:Python4612

• bips-hb/StatMed_MissingCausalDiscovery

  Language:R1

• abreschi/shinySpecClust

  Language:R36

• thuml/Time-Series-Library

  A Library for Advanced Deep Time Series Models for General Time Series Analysis.

  Language:Python10k1.6k

• SunSeaLucky/CHARLS

  Language:Python4

• zhihanyue/ts2vec

  A universal time series representation learning framework

  Language:Python755173