van_der_Schaar \LAB
We are creating cutting-edge machine learning methods and applying them to drive a revolution in healthcare.
Pinned Repositories
autoprognosis
A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
clairvoyance
Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series
Datagnosis
A Data-Centric library providing a unified interface for state-of-the-art methods for hardness characterisation of data points.
evaluating-generative-models
hyperimpute
A framework for prototyping and benchmarking imputation methods
Interpretability
Resources for Machine Learning Explainability
MIRACLE
mlforhealthlabpub
Machine Learning and Artificial Intelligence for Medicine.
synthcity
A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.
temporai
TemporAI: ML-centric Toolkit for Medical Time Series
van_der_Schaar \LAB's Repositories
vanderschaarlab/synthcity
A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.
vanderschaarlab/autoprognosis
A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
vanderschaarlab/Interpretability
Resources for Machine Learning Explainability
vanderschaarlab/MIRACLE
vanderschaarlab/Datagnosis
A Data-Centric library providing a unified interface for state-of-the-art methods for hardness characterisation of data points.
vanderschaarlab/synthetic-data-lab
A repository containing the materials required to complete the "AAAI Lab for Innovative Uses of Synthetic Data". This includes tutorials on how to use the library "Synthcity" for improving the fairness and privacy of a dataset as well as for augmenting a small dataset using some other similar datasets.
vanderschaarlab/CCAIM-Synthetic-data-tutorial
The GitHub Repo for the hands-on session at NLDL entitled "Tutorial: Innovative Uses of Synthetic Data Tutorial".
vanderschaarlab/GOGGLE
vanderschaarlab/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'.
vanderschaarlab/NeuralLaplace
Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
vanderschaarlab/AutoPrognosis-Multimodal
AutoPrognosis with imaging data
vanderschaarlab/H-CAT
vanderschaarlab/L2MAC
🚀 The LLM Automatic Computer Framework: L2MAC
vanderschaarlab/TIMEVIEW
vanderschaarlab/CATESelection
Sklearn-style implementations of model selection criteria for CATE estimation
vanderschaarlab/joint-ensembles
vanderschaarlab/TRIAGE
TRIAGE: Characterizing and auditing training data for improved regression
vanderschaarlab/ActiveObservingInContinuous-timeControl
Active Observing in Continuous-time Control
vanderschaarlab/attention-based-credit
Code for the paper: Dense Reward for Free in Reinforcement Learning from Human Feedback (ICML 2024) by Alex J. Chan, Hao Sun, Samuel Holt, and Mihaela van der Schaar
vanderschaarlab/CLLM
Curated LLM (ICML 2024)
vanderschaarlab/DAGNOSIS
vanderschaarlab/demo-interpretability
vanderschaarlab/epdm
vanderschaarlab/Expertise
Defining Expertise: Applications to Treatment Effect Estimation
vanderschaarlab/LLAMBO
Official Repository for LLAMBO "Large Language Models to Enhance Bayesian Optimization"
vanderschaarlab/ODE-Discovery-for-Longitudinal-Heterogeneous-Treatment-Effects-Inference
ODEDiscoveryforLongitudinalHeterogeneousTreatmentEffectsInference
vanderschaarlab/Prompt-OIRL
code for paper Query-Dependent Prompt Evaluation and Optimization with Offline Inverse Reinforcement Learning
vanderschaarlab/smd
vanderschaarlab/syntax
Adaptive Experiment Design with Synthetic Controls
vanderschaarlab/TESAR-CDE
Code for the paper "Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time" (ICML 2023)