Jinsung Yoon

According to our database1, Jinsung Yoon authored at least 34 papers between 2015 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2019
Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks.
IEEE Trans. Biomed. Engineering, 2019

RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling.
CoRR, 2019

Data Valuation using Reinforcement Learning.
CoRR, 2019

ASAC: Active Sensing using Actor-Critic models.
CoRR, 2019

INVASE: Instance-wise Variable Selection using Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees.
Proceedings of the 7th International Conference on Learning Representations, 2019

KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Design of a Dynamic Data-Driven System for Multispectral Video Processing.
Proceedings of the Handbook of Dynamic Data Driven Applications Systems., 2018

ToPs: Ensemble Learning With Trees of Predictors.
IEEE Trans. Signal Processing, 2018

Personalized Risk Scoring for Critical Care Prognosis Using Mixtures of Gaussian Processes.
IEEE Trans. Biomed. Engineering, 2018

MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks.
CoRR, 2018

Feature Selection for Survival Analysis with Competing Risks using Deep Learning.
CoRR, 2018

Measuring the quality of Synthetic data for use in competitions.
CoRR, 2018

GAIN: Missing Data Imputation using Generative Adversarial Nets.
CoRR, 2018

RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks.
CoRR, 2018

RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

GAIN: Missing Data Imputation using Generative Adversarial Nets.
Proceedings of the 35th International Conference on Machine Learning, 2018

Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets.
Proceedings of the 6th International Conference on Learning Representations, 2018

DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Adaptive Ensemble Learning With Confidence Bounds.
IEEE Trans. Signal Processing, 2017

Discovery and Clinical Decision Support for Personalized Healthcare.
IEEE J. Biomedical and Health Informatics, 2017

Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks.
CoRR, 2017

ToPs: Ensemble Learning with Trees of Predictors.
CoRR, 2017

Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors.
CoRR, 2017

Individualized Risk Prognosis for Critical Care Patients: A Multi-task Gaussian Process Model.
CoRR, 2017

Personalized Donor-Recipient Matching for Organ Transplantation.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Personalized Donor-Recipient Matching for Organ Transplantation.
CoRR, 2016

A Semi-Markov Switching Linear Gaussian Model for Censored Physiological Data.
CoRR, 2016

Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes.
CoRR, 2016

Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts.
CoRR, 2016

ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Adaptive Ensemble Learning with Confidence Bounds for Personalized Diagnosis.
Proceedings of the Expanding the Boundaries of Health Informatics Using AI, 2016

2015
Adaptive Ensemble Learning with Confidence Bounds.
CoRR, 2015


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