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/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/climb
CliMB: An AI-enabled Partner for Clinical Predictive Modeling
vanderschaarlab/Data-IQ
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data
vanderschaarlab/CATENets
Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
vanderschaarlab/NeuralLaplace
Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
vanderschaarlab/Simplex
This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.
vanderschaarlab/DeepGenerativeSymbolicRegression
Deep Generative Symbolic Regression Code
vanderschaarlab/L2MAC
🚀 The LLM Automatic Computer Framework: L2MAC
vanderschaarlab/TRIAGE
TRIAGE: Characterizing and auditing training data for improved regression
vanderschaarlab/conformal-rnn
Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
vanderschaarlab/Data-SUITE
Data-SUITE: Data-centric identification of in-distribution incongruous examples
vanderschaarlab/mcm
To Impute or not to Impute? Missing Data in Treatment Effect Estimation
vanderschaarlab/medkit-learn
The Medkit-Learn(ing) Environment. An open-source library for offline sequential decision making with a focus on medicine.
vanderschaarlab/optcommit
When to make and break commitments?
vanderschaarlab/tphenotype
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/cvar_sensing
vanderschaarlab/D-CIPHER
vanderschaarlab/DAGNOSIS
vanderschaarlab/HDTwinGen
vanderschaarlab/NeuralLaplaceControl
Neural Laplace Control
vanderschaarlab/POCA
vanderschaarlab/Self_Healing_ML
vanderschaarlab/SMART_Testing