Jinsung Yoon

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 94

Top Topics

Missing Data Imputation

Top Venues

Trans. Mach. Learn. Res.

Publications

Zachary Izzo, Jinsung Yoon, Sercan Ö. Arik, James Zou
Provable Membership Inference Privacy. Trans. Mach. Learn. Res. 2024 (2024)
Jinsung Yoon, Yanfei Chen, Sercan Ö. Arik, Tomas Pfister
Search-Adaptor: Embedding Customization for Information Retrieval. ACL (1) (2024)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. Trans. Mach. Learn. Res. 2024 (2024)
Hyunsung Kim, Gun-Hee Joe, Jinsung Yoon, Sang-Ki Ko
Contextual Sprint Classification in Soccer Based on Deep Learning. CoRR (2024)
Sungwon Han, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning. CoRR (2024)
Sung-Jin Lee, Bit Kim, Dong-Wook Yang, Junseo Kim, Tom Parkinson, Johsan Billingham, Chulwoo Park, Jinsung Yoon, Dae-Young Lee
A compact RTK-GNSS device for high-precision localization of outdoor mobile robots. J. Field Robotics 41 (5) (2024)
Hongjin Su, Howard Yen, Mengzhou Xia, Weijia Shi, Niklas Muennighoff, Han-yu Wang, Haisu Liu, Quan Shi, Zachary S. Siegel, Michael Tang, Ruoxi Sun, Jinsung Yoon, Sercan Ö. Arik, Danqi Chen, Tao Yu
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval. CoRR (2024)
Jinsung Yoon, Rajarishi Sinha, Sercan Ö. Arik, Tomas Pfister
Matryoshka-Adaptor: Unsupervised and Supervised Tuning for Smaller Embedding Dimensions. CoRR (2024)
Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister
Data-Efficient and Interpretable Tabular Anomaly Detection. KDD (2023)
Hyunsung Kim, Han-Jun Choi, Chang Jo Kim, Jinsung Yoon, Sang-Ki Ko
Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM. KDD (2023)
Jinsung Yoon, Donghyun Lee, Neungyun Kim, Su-Jung Lee, Gil-Ho Kwak, Tae-Hwan Kim
A Real-Time Keyword Spotting System Based on an End-To-End Binary Convolutional Neural Network in FPGA. COOL CHIPS (2023)
Min Jae Lee, Kyunghoon Hur, Jiyoun Kim, Jinsung Yoon, Edward Choi
Rediscovery of CNN's Versatility for Text-based Encoding of Raw Electronic Health Records. CHIL (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. CoRR (2023)
Hyunsung Kim, Han-Jun Choi, Chang Jo Kim, Jinsung Yoon, Sang-Ki Ko
Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM. CoRR (2023)
Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. WACV (2023)
Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
Clairvoyance: A Pipeline Toolkit for Medical Time Series. CoRR (2023)
Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister
Invariant Structure Learning for Better Generalization and Causal Explainability. Trans. Mach. Learn. Res. 2023 (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. CoRR (2023)
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. Trans. Mach. Learn. Res. 2023 (2023)
Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister
Interpretable Mixture of Experts. Trans. Mach. Learn. Res. 2023 (2023)
Jinsung Yoon, Sercan Ö. Arik, Yanfei Chen, Tomas Pfister
Search-Adaptor: Text Embedding Customization for Information Retrieval. CoRR (2023)
Mingu Kim, Chulwoo Park, Jinsung Yoon
The Design of GNSS/IMU Loosely-Coupled Integration Filter for Wearable EPTS of Football Players. Sensors 23 (4) (2023)
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
EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records. npj Digit. Medicine 6 (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö Arik, Tomas Pfister, Somesh Jha
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. EMNLP (Findings) (2023)
Eunbyeol Cho, Min Jae Lee, Kyunghoon Hur, Jiyoun Kim, Jinsung Yoon, Edward Choi
Rediscovery of CNN's Versatility for Text-based Encoding of Raw Electronic Health Records. CoRR (2023)
Nicasia Beebe-Wang, Sayna Ebrahimi, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister
PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series. CoRR (2023)
Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister
Interpretable Mixture of Experts for Structured Data. CoRR (2022)
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection. Trans. Mach. Learn. Res. 2022 (2022)
Jeongbin Kim, Hyunsung Kim, Jonghyun Lee, Jaechan Lee, Jinsung Yoon, Sang-Ki Ko
A Deep Learning Approach for Fatigue Prediction in Sports Using GPS Data and Rate of Perceived Exertion. IEEE Access 10 (2022)
Hyunsung Kim, Bit Kim, Dongwook Chung, Jinsung Yoon, Sang-Ki Ko
SoccerCPD: Formation and Role Change-Point Detection in Soccer Matches Using Spatiotemporal Tracking Data. KDD (2022)
Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister
Data-Efficient and Interpretable Tabular Anomaly Detection. CoRR (2022)
Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister
Invariant Structure Learning for Better Generalization and Causal Explainability. CoRR (2022)
Thomas C. Tsai, Sercan Ö. Arik, Benjamin H. Jacobson, Jinsung Yoon, Nate Yoder, Dario Sava, Margaret Mitchell, Garth Graham, Tomas Pfister
Algorithmic fairness in pandemic forecasting: lessons from COVID-19. npj Digit. Medicine 5 (2022)
Zachary Izzo, Jinsung Yoon, Sercan Ö. Arik, James Zou
Provable Membership Inference Privacy. CoRR (2022)
Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister
LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling. Trans. Mach. Learn. Res. 2022 (2022)
Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister
Towards Group Robustness in the presence of Partial Group Labels. CoRR (2022)
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. CoRR (2022)
Hyunsung Kim, Chang Jo Kim, Minchul Jeong, Jaechan Lee, Jinsung Yoon, Sang-Ki Ko
Cost-Efficient and Bias-Robust Sports Player Tracking by Integrating GPS and Video. MLSA@PKDD/ECML (2022)
Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. CoRR (2021)
Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister
Controlling Neural Networks with Rule Representations. NeurIPS (2021)
Hyunsung Kim, Jihun Kim, Dongwook Chung, Jonghyun Lee, Jinsung Yoon, Sang-Ki Ko
6MapNet: Representing soccer players from tracking data by a triplet network. CoRR (2021)
Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CVPR (2021)
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister
Self-Trained One-class Classification for Unsupervised Anomaly Detection. CoRR (2021)
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
A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. npj Digit. Medicine 4 (2021)
Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
Clairvoyance: A Pipeline Toolkit for Medical Time Series. ICLR (2021)
Hyunsung Kim, Jihun Kim, Dongwook Chung, Jonghyun Lee, Jinsung Yoon, Sang-Ki Ko
6MapNet: Representing Soccer Players from Tracking Data by a Triplet Network. MLSA@PKDD/ECML (2021)
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
Learning and Evaluating Representations for Deep One-Class Classification. ICLR (2021)
Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CoRR (2021)
Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister
Controlling Neural Networks with Rule Representations. CoRR (2021)
James Jordon, Daniel Jarrett, Evgeny Saveliev, Jinsung Yoon, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar
Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification. NeurIPS (Competition and Demos) (2020)
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
Learning and Evaluating Representations for Deep One-class Classification. CoRR (2020)
Changhee Lee, Jinsung Yoon, Mihaela van der Schaar
Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data. IEEE Trans. Biomed. Eng. 67 (1) (2020)
Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister
Data Valuation using Reinforcement Learning. ICML (2020)
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
Interpretable Sequence Learning for COVID-19 Forecasting. CoRR (2020)
Jinsung Yoon, Lydia N. Drumright, Mihaela van der Schaar
Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN). IEEE J. Biomed. Health Informatics 24 (8) (2020)
Jinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar
VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain. NeurIPS (2020)
James Jordon, Daniel Jarrett, Jinsung Yoon, Tavian Barnes, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar
Hide-and-Seek Privacy Challenge. CoRR (2020)
Daniel Jarrett, Jinsung Yoon, Mihaela van der Schaar
Dynamic Prediction in Clinical Survival Analysis Using Temporal Convolutional Networks. IEEE J. Biomed. Health Informatics 24 (2) (2020)
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
Interpretable Sequence Learning for Covid-19 Forecasting. NeurIPS (2020)
Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister
Data Valuation using Reinforcement Learning. CoRR (2019)
Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister
RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling. CoRR (2019)
James Jordon, Jinsung Yoon, Mihaela van der Schaar
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate. NeurIPS (2019)
James Jordon, Jinsung Yoon, Mihaela van der Schaar
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks. ICLR (2019)
Jinsung Yoon, James Jordon, Mihaela van der Schaar
INVASE: Instance-wise Variable Selection using Neural Networks. ICLR (Poster) (2019)
Jinsung Yoon, Daniel Jarrett, Mihaela van der Schaar
Time-series Generative Adversarial Networks. NeurIPS (2019)
James Jordon, Jinsung Yoon, Mihaela van der Schaar
PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees. ICLR (Poster) (2019)
Jinsung Yoon, James Jordon, Mihaela van der Schaar
ASAC: Active Sensing using Actor-Critic models. CoRR (2019)
Jinsung Yoon, James Jordon, Mihaela van der Schaar
ASAC: Active Sensing using Actor-Critic models. MLHC (2019)
Jinsung Yoon, William R. Zame, Mihaela van der Schaar
Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks. IEEE Trans. Biomed. Eng. 66 (5) (2019)
James Jordon, Jinsung Yoon, Mihaela van der Schaar
Measuring the quality of Synthetic data for use in competitions. CoRR (2018)
Jinsung Yoon, James Jordon, Mihaela van der Schaar
GAIN: Missing Data Imputation using Generative Adversarial Nets. CoRR (2018)
Carl Rietschel, Jinsung Yoon, Mihaela van der Schaar
Feature Selection for Survival Analysis with Competing Risks using Deep Learning. CoRR (2018)
Jinsung Yoon, James Jordon, Mihaela van der Schaar
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. ICML (2018)
Jinsung Yoon, James Jordon, Mihaela van der Schaar
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. CoRR (2018)
Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar
Personalized Risk Scoring for Critical Care Prognosis Using Mixtures of Gaussian Processes. IEEE Trans. Biomed. Eng. 65 (1) (2018)
Jinsung Yoon, William R. Zame, Mihaela van der Schaar
Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks. ICLR (Poster) (2018)
Changhee Lee, William R. Zame, Jinsung Yoon, Mihaela van der Schaar
DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks. AAAI (2018)
Daniel Jarrett, Jinsung Yoon, Mihaela van der Schaar
MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks. CoRR (2018)
Jinsung Yoon, William R. Zame, Mihaela van der Schaar
ToPs: Ensemble Learning With Trees of Predictors. IEEE Trans. Signal Process. 66 (8) (2018)
Jinsung Yoon, James Jordon, Mihaela van der Schaar
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets. ICLR (Poster) (2018)
Jinsung Yoon, James Jordon, Mihaela van der Schaar
GAIN: Missing Data Imputation using Generative Adversarial Nets. ICML (2018)
Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar
Individualized Risk Prognosis for Critical Care Patients: A Multi-task Gaussian Process Model. CoRR (2017)
Cem Tekin, Jinsung Yoon, Mihaela van der Schaar
Adaptive Ensemble Learning With Confidence Bounds. IEEE Trans. Signal Process. 65 (4) (2017)
Jinsung Yoon, Ahmed M. Alaa, Martin Cadeiras, Mihaela van der Schaar
Personalized Donor-Recipient Matching for Organ Transplantation. AAAI (2017)
Jinsung Yoon, William R. Zame, Mihaela van der Schaar
Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks. CoRR (2017)
Jinsung Yoon, William R. Zame, Mihaela van der Schaar
ToPs: Ensemble Learning with Trees of Predictors. CoRR (2017)
Jinsung Yoon, Camelia Davtyan, Mihaela van der Schaar
Discovery and Clinical Decision Support for Personalized Healthcare. IEEE J. Biomed. Health Informatics 21 (4) (2017)
Jinsung Yoon, William R. Zame, Amitava Banerjee, Martin Cadeiras, Ahmed M. Alaa, Mihaela van der Schaar
Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors. CoRR (2017)
Jinsung Yoon, Ahmed M. Alaa, Scott Hu, Mihaela van der Schaar
ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission. ICML (2016)
Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar
Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes. CoRR (2016)
Cem Tekin, Jinsung Yoon, Mihaela van der Schaar
Adaptive Ensemble Learning with Confidence Bounds for Personalized Diagnosis. AAAI Workshop: Expanding the Boundaries of Health Informatics Using AI (2016)
Jinsung Yoon, Ahmed M. Alaa, Martin Cadeiras, Mihaela van der Schaar
Personalized Donor-Recipient Matching for Organ Transplantation. CoRR (2016)
Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar
A Semi-Markov Switching Linear Gaussian Model for Censored Physiological Data. CoRR (2016)
Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar
Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts. CoRR (2016)
Cem Tekin, Jinsung Yoon, Mihaela van der Schaar
Adaptive Ensemble Learning with Confidence Bounds. CoRR (2015)