Jinsung Yoon

According to our database, Jinsung Yoon authored at least 68 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

The Design of GNSS/IMU Loosely-Coupled Integration Filter for Wearable EPTS of Football Players.

Mingu Kim, Chulwoo Park, Jinsung Yoon

Sensors, February, 2023

SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch.

Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister

Trans. Mach. Learn. Res., 2023

EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records.

Jinsung Yoon, Michel J. Mizrahi, Nahid Farhady Ghalaty, Thomas Jarvinen, Ashwin S. Ravi, Peter Brune, Fanyu Kong, Dave Anderson, George Lee, Arie Meir, Farhana Bandukwala, Elli Kanal, Sercan Ö. Arik, Tomas Pfister

npj Digit. Medicine, 2023

Search-Adaptor: Text Embedding Customization for Information Retrieval.

Jinsung Yoon, Sercan Ö. Arik, Yanfei Chen, Tomas Pfister

CoRR, 2023

PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series.

Nicasia Beebe-Wang, Sayna Ebrahimi, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister

CoRR, 2023

ASPEST: Bridging the Gap Between Active Learning and Selective Prediction.

Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister

CoRR, 2023

Rediscovery of CNN's Versatility for Text-based Encoding of Raw Electronic Health Records.

Eunbyeol Cho, Min Jae Lee, Kyunghoon Hur, Jiyoun Kim, Jinsung Yoon, Edward Choi

CoRR, 2023

Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types.

Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Data-Efficient and Interpretable Tabular Anomaly Detection.

Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM.

Hyunsung Kim, Han-Jun Choi, Chang Jo Kim, Jinsung Yoon, Sang-Ki Ko

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs.

Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

A Real-Time Keyword Spotting System Based on an End-To-End Binary Convolutional Neural Network in FPGA.

Jinsung Yoon, Donghyun Lee, Neungyun Kim, Su-Jung Lee, Gil-Ho Kwak, Tae-Hwan Kim

Proceedings of the IEEE Symposium in Low-Power and High-Speed Chips, 2023

Rediscovery of CNN's Versatility for Text-based Encoding of Raw Electronic Health Records.

Min Jae Lee, Kyunghoon Hur, Jiyoun Kim, Jinsung Yoon, Edward Choi

Proceedings of the Conference on Health, Inference, and Learning, 2023

2022

Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection.

Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister

Trans. Mach. Learn. Res., 2022

LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling.

Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister

Trans. Mach. Learn. Res., 2022

Algorithmic fairness in pandemic forecasting: lessons from COVID-19.

Thomas C. Tsai, Sercan Ö. Arik, Benjamin H. Jacobson, Jinsung Yoon, Nate Yoder, Dario Sava, Margaret Mitchell, Garth Graham, Tomas Pfister

npj Digit. Medicine, 2022

Provable Membership Inference Privacy.

Zachary Izzo, Jinsung Yoon, Sercan Ö. Arik, James Zou

CoRR, 2022

Invariant Structure Learning for Better Generalization and Causal Explainability.

Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister

CoRR, 2022

Interpretable Mixture of Experts for Structured Data.

Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister

CoRR, 2022

Towards Group Robustness in the presence of Partial Group Labels.

Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister

CoRR, 2022

A Deep Learning Approach for Fatigue Prediction in Sports Using GPS Data and Rate of Perceived Exertion.

Jeongbin Kim, Hyunsung Kim, Jonghyun Lee, Jaechan Lee, Jinsung Yoon, Sang-Ki Ko

IEEE Access, 2022

Cost-Efficient and Bias-Robust Sports Player Tracking by Integrating GPS and Video.

Hyunsung Kim, Chang Jo Kim, Minchul Jeong, Jaechan Lee, Jinsung Yoon, Sang-Ki Ko

Proceedings of the Machine Learning and Data Mining for Sports Analytics, 2022

SoccerCPD: Formation and Role Change-Point Detection in Soccer Matches Using Spatiotemporal Tracking Data.

Hyunsung Kim, Bit Kim, Dongwook Chung, Jinsung Yoon, Sang-Ki Ko

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan.

Sercan Ö. Arik, Joel Shor, Rajarishi Sinha, Jinsung Yoon, Joseph R. Ledsam, Long T. Le, Michael W. Dusenberry, Nathanael C. Yoder, Kris Popendorf, Arkady Epshteyn, Johan Euphrosine, Elli Kanal, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Shashank Singh, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang, Dario Sava, Kane Cunningham, Hiroki Kayama, Thomas C. Tsai, Daisuke Yoneoka, Shuhei Nomura, Hiroaki Miyata, Tomas Pfister

npj Digit. Medicine, 2021

Self-Trained One-class Classification for Unsupervised Anomaly Detection.

Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister

CoRR, 2021

6MapNet: Representing Soccer Players from Tracking Data by a Triplet Network.

Hyunsung Kim, Jihun Kim, Dongwook Chung, Jonghyun Lee, Jinsung Yoon, Sang-Ki Ko

Proceedings of the Machine Learning and Data Mining for Sports Analytics, 2021

Controlling Neural Networks with Rule Representations.

Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning and Evaluating Representations for Deep One-Class Classification.

Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister

Proceedings of the 9th International Conference on Learning Representations, 2021

Clairvoyance: A Pipeline Toolkit for Medical Time Series.

Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar

Proceedings of the 9th International Conference on Learning Representations, 2021

CutPaste: Self-Supervised Learning for Anomaly Detection and Localization.

Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

End-to-End Machine Learning Frameworks for Medicine: Data Imputation, Model Interpretation and Synthetic Data Generation.

Jinsung Yoon

PhD thesis, 2020

Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN).

Jinsung Yoon, Lydia N. Drumright, Mihaela van der Schaar

IEEE J. Biomed. Health Informatics, 2020

Dynamic Prediction in Clinical Survival Analysis Using Temporal Convolutional Networks.

Daniel Jarrett, Jinsung Yoon, Mihaela van der Schaar

IEEE J. Biomed. Health Informatics, 2020

Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data.

Changhee Lee, Jinsung Yoon, Mihaela van der Schaar

IEEE Trans. Biomed. Eng., 2020

Interpretable Sequence Learning for COVID-19 Forecasting.

Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister

CoRR, 2020

Hide-and-Seek Privacy Challenge.

James Jordon, Daniel Jarrett, Jinsung Yoon, Tavian Barnes, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar

CoRR, 2020

VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain.

Jinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification.

James Jordon, Daniel Jarrett, Evgeny Saveliev, Jinsung Yoon, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Interpretable Sequence Learning for Covid-19 Forecasting.

Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Data Valuation using Reinforcement Learning.

Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks.

Jinsung Yoon, William R. Zame, Mihaela van der Schaar

IEEE Trans. Biomed. Eng., 2019

RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling.

Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister

CoRR, 2019

Time-series Generative Adversarial Networks.

Jinsung Yoon, Daniel Jarrett, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate.

James Jordon, Jinsung Yoon, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

ASAC: Active Sensing using Actor-Critic models.

Jinsung Yoon, James Jordon, Mihaela van der Schaar

Proceedings of the Machine Learning for Healthcare Conference, 2019

INVASE: Instance-wise Variable Selection using Neural Networks.

Jinsung Yoon, James Jordon, Mihaela van der Schaar

Proceedings of the 7th International Conference on Learning Representations, 2019

PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees.

James Jordon, Jinsung Yoon, Mihaela van der Schaar

Proceedings of the 7th International Conference on Learning Representations, 2019

KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks.

James Jordon, Jinsung Yoon, Mihaela van der Schaar

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Design of a Dynamic Data-Driven System for Multispectral Video Processing.

Honglei Li, Yanzhou Liu, Kishan Sudusinghe, Jinsung Yoon, Erik Blasch, Mihaela van der Schaar, Shuvra S. Bhattacharyya

Proceedings of the Handbook of Dynamic Data Driven Applications Systems., 2018

ToPs: Ensemble Learning With Trees of Predictors.

Jinsung Yoon, William R. Zame, Mihaela van der Schaar

IEEE Trans. Signal Process., 2018

Personalized Risk Scoring for Critical Care Prognosis Using Mixtures of Gaussian Processes.

Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar

IEEE Trans. Biomed. Eng., 2018

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

Daniel Jarrett, Jinsung Yoon, Mihaela van der Schaar

CoRR, 2018

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

Carl Rietschel, Jinsung Yoon, Mihaela van der Schaar

CoRR, 2018

Measuring the quality of Synthetic data for use in competitions.

James Jordon, Jinsung Yoon, Mihaela van der Schaar

CoRR, 2018

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

Jinsung Yoon, James Jordon, Mihaela van der Schaar

Proceedings of the 35th International Conference on Machine Learning, 2018

GAIN: Missing Data Imputation using Generative Adversarial Nets.

Jinsung Yoon, James Jordon, Mihaela van der Schaar

Proceedings of the 35th International Conference on Machine Learning, 2018

Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks.

Jinsung Yoon, William R. Zame, Mihaela van der Schaar

Proceedings of the 6th International Conference on Learning Representations, 2018

GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets.

Jinsung Yoon, James Jordon, Mihaela van der Schaar

Proceedings of the 6th International Conference on Learning Representations, 2018

DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks.

Changhee Lee, William R. Zame, Jinsung Yoon, Mihaela van der Schaar

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Adaptive Ensemble Learning With Confidence Bounds.

Cem Tekin, Jinsung Yoon, Mihaela van der Schaar

IEEE Trans. Signal Process., 2017

Discovery and Clinical Decision Support for Personalized Healthcare.

Jinsung Yoon, Camelia Davtyan, Mihaela van der Schaar

IEEE J. Biomed. Health Informatics, 2017

Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors.

Jinsung Yoon, William R. Zame, Amitava Banerjee, Martin Cadeiras, Ahmed M. Alaa, Mihaela van der Schaar

CoRR, 2017

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

Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar

CoRR, 2017

Personalized Donor-Recipient Matching for Organ Transplantation.

Jinsung Yoon, Ahmed M. Alaa, Martin Cadeiras, Mihaela van der Schaar

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

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

Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar

CoRR, 2016

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

Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar

CoRR, 2016

ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission.

Jinsung Yoon, Ahmed M. Alaa, Scott Hu, Mihaela van der Schaar

Proceedings of the 33nd International Conference on Machine Learning, 2016

Adaptive Ensemble Learning with Confidence Bounds for Personalized Diagnosis.

Cem Tekin, Jinsung Yoon, Mihaela van der Schaar

Proceedings of the Expanding the Boundaries of Health Informatics Using AI, 2016