The lab
Mihaela van der Schaar
Research team
Funding
Clinical partners
Publications
Big ideas
News
Videos
Events
Software
Demonstrators
Overview
Demonstrator: Synthetic Data
Demonstrator: Survival Analysis
Engagement sessions
Inspiration Exchange
Revolutionizing Healthcare
2021 open house
WeCREATE
Tutorials
AAAI-22: Time series in healthcare
Individualized treatment effect inference
ICML 2021: Synthetic Healthcare Data Generation and Assessment
ICML 2020: Machine Learning for Healthcare: Challenges, Methods, and Frontiers
Research pillars
Automated machine learning
Causal deep learning
Clustering
Individualized treatment effect inference
Interpretable ML
Next-gen clinical trials
Quantitative epistemology
Self-supervised, semi-supervised, and multi-view learning
Survival analysis, competing risks, and comorbidities
Synthetic data
Overview
Privacy challenge
Time series
Trustworthy and robust ML (in progress)
Uncertainty quantification
Impact
Our lab’s impact
Demonstrators
Overview
Demonstrator: Synthetic Data
Demonstrator: Survival Analysis
Alzheimer’s
Cancer
Our projects
Prostate Cancer
Breast cancer
COVID-19
Our projects
Announcements
Policy Impact Predictor
Cystic fibrosis
Early detection and diagnosis
Organ transplantation
Hub for Healthcare
Contact
Ph.D. applications
2022 work placement
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Category - NeurIPS
van der Schaar Lab at NeurIPS 2022: 7 papers and 2 workshops
Andreas Bedorf
September 21, 2022
SyntheticData4ML Workshop
Andreas Bedorf
August 10, 2022
The lab
Mihaela van der Schaar
Research team
Funding
Clinical partners
Publications
Big ideas
News
Videos
Events
Software
Demonstrators
Overview
Demonstrator: Synthetic Data
Demonstrator: Survival Analysis
Engagement sessions
Inspiration Exchange
Revolutionizing Healthcare
2021 open house
WeCREATE
Tutorials
AAAI-22: Time series in healthcare
Individualized treatment effect inference
ICML 2021: Synthetic Healthcare Data Generation and Assessment
ICML 2020: Machine Learning for Healthcare: Challenges, Methods, and Frontiers
Research pillars
Automated machine learning
Causal deep learning
Clustering
Individualized treatment effect inference
Interpretable ML
Next-gen clinical trials
Quantitative epistemology
Self-supervised, semi-supervised, and multi-view learning
Survival analysis, competing risks, and comorbidities
Synthetic data
Overview
Privacy challenge
Time series
Trustworthy and robust ML (in progress)
Uncertainty quantification
Impact
Our lab’s impact
Demonstrators
Overview
Demonstrator: Synthetic Data
Demonstrator: Survival Analysis
Alzheimer’s
Cancer
Our projects
Prostate Cancer
Breast cancer
COVID-19
Our projects
Announcements
Policy Impact Predictor
Cystic fibrosis
Early detection and diagnosis
Organ transplantation
Hub for Healthcare
Contact
Ph.D. applications
2022 work placement
Andreas Bedorf