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06/15/2023
Multi-omics Prediction from High-content Cellular Imaging with Deep Learning
High-content cellular imaging, transcriptomics, and proteomics data prov...
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11/07/2022
FED-CD: Federated Causal Discovery from Interventional and Observational Data
Causal discovery, the inference of causal relations from data, is a core...
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10/31/2022
CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data
Mapping biological mechanisms in cellular systems is a fundamental step ...
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04/20/2022
Federated Learning in Multi-Center Critical Care Research: A Systematic Case Study using the eICU Database
Federated learning (FL) has been proposed as a method to train a model o...
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01/20/2022
Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations
The widespread adoption of electronic health records (EHRs) and subseque...
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10/22/2021
GeneDisco: A Benchmark for Experimental Design in Drug Discovery
In vitro cellular experimentation with genetic interventions, using for ...
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09/06/2021
Learning Neural Causal Models with Active Interventions
Discovering causal structures from data is a challenging inference probl...
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03/20/2021
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments
Estimating an individual's potential response to interventions from obse...
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08/31/2020
Real-time Prediction of COVID-19 related Mortality using Electronic Health Records
Coronavirus Disease 2019 (COVID-19) is an emerging respiratory disease c...
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05/17/2020
predCOVID-19: A Systematic Study of Clinical Predictive Models for Coronavirus Disease 2019
Coronavirus Disease 2019 (COVID-19) is a rapidly emerging respiratory di...
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01/02/2020
A Deep Learning Approach to Diagnosing Multiple Sclerosis from Smartphone Data
Multiple sclerosis (MS) affects the central nervous system with a wide r...
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10/27/2019
CXPlain: Causal Explanations for Model Interpretation under Uncertainty
Feature importance estimates that inform users about the degree to which...
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02/03/2019
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves
Estimating what would be an individual's potential response to varying l...
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10/01/2018
Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks
Learning representations for counterfactual inference from observational...
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10/01/2018
PhoneMD: Learning to Diagnose Parkinson's Disease from Smartphone Data
Parkinson's disease is a neurodegenerative disease that can affect a per...
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02/14/2018
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patients in the intensive care unit (ICU) require constant and close sup...
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02/06/2018
Granger-causal Attentive Mixtures of Experts
Several methods have recently been proposed to detect salient input feat...
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10/17/2017