vanderschaarlab Goto Github PK

dynamask

This repository contains the implementation of Dynamask, a method to identify the features that are salient for a model to issue its prediction when the data is represented in terms of time series. For more details on the theoretical side, please read our ICML 2021 paper: 'Explaining Time Series Predictions with Dynamic Masks'.

ebm-for-cate

Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects

epdm

evaluating-generative-models

expertise

Defining Expertise: Applications to Treatment Effect Estimation

fourier-flows

Generative Time-series Modeling with Fourier Flows

goggle

graphical-modelling-continuous-time

Graphical modelling with time series data using an ODE model

h-cat

hide-and-seek-submissions

Repository of NeurIPS 2020 "Hide-and-Seek" competition submissions.

htce-learners

Code for NeurIPS 2022 paper: "Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation" by I. Bica, M. van der Schaar

hybrid-ode-neurips-2021

Code for Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression (NeurIPS 2021)

hyperimpute

A framework for prototyping and benchmarking imputation methods

interpretability

Resources for Machine Learning Explainability

invariant-causal-imitation-learning

Code for NeurIPS 2021 paper: "Invariant Causal Imitation Learning for Generalizable Policies" by I. Bica, D. Jarrett, M. van der Schaar

invase

INVASE: Instance-wise Variable Selection . For more details, read the paper "INVASE: Instance-wise Variable Selection using Neural Networks," International Conference on Learning Representations (ICLR), 2019.

invconban

inverse-online

Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies (ICLR 2022) by Alex J. Chan, Alicia Curth, and Mihaela van der Schaar

iterpretability

This repository contains the implementation of ITErpretability, a new framework to benchmark treatment effect deep neural network estimators with interpretability. For more details, please read our NeurIPS 2022 paper: 'Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability'.

joint-ensembles

label-free-xai

This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For more details, please read our ICML 2022 paper: 'Label-Free Explainability for Unsupervised Models'.

legato

llambo

Official Repository for LLAMBO "Large Language Models to Enhance Bayesian Optimization"

lori

Inferring Lexicographically-Ordered Rewards from Preferences

mcm

To Impute or not to Impute? Missing Data in Treatment Effect Estimation

medkit-learn

The Medkit-Learn(ing) Environment. An open-source library for offline sequential decision making with a focus on medicine.

mimic-iv-data-pipeline

A customizable pipeline for data extraction from MIMIC-IV.

miracle

ml-as-prostate-cancer

Code repository for paper "Development and clinical utility of machine learning algorithms for dynamic longitudinal real-time estimation of progression risks in active surveillance of early prostate cancer"

mlforhealthlabpub

Machine Learning and Artificial Intelligence for Medicine.