Jonathan Rubin

Publication Activity (10 Years)

Years Active: 2007-2023
Publications (10 Years): 35

Top Topics

Role Playing Game

Ischemic Stroke

Lesion Segmentation

Top Venues

Int. J. Medical Informatics

Publications

Nicholas Theis, Jonathan Rubin, Joshua Cape, Satish Iyengar, Konasale M. Prasad
Threshold Selection for Brain Connectomes. Brain Connect. 13 (7) (2023)
Jonathan Rubin, Jason Crowley, George Leung, Morteza Ziyadi, Maria Minakova
Entity Contrastive Learning in a Large-Scale Virtual Assistant System. ACL (industry) (2023)
Li Chen, Jonathan Rubin, Jiahong Ouyang, Naveen Balaraju, Shubham Patil, Courosh Mehanian, Sourabh Kulhare, Rachel Millin, Kenton W. Gregory, Cynthia Gregory, Meihua Zhu, David O. Kessler, Laurie Malia, Almaz Dessie, Joni Rabiner, Di Coneybeare, Bo Shopsin, Andrew Hersh, Cristian Madar, Jeffrey Shupp, Laura S. Johnson, Jacob Avila, Kristin Dwyer, Peter Weimersheimer, Balasundar Raju, Jochen Kruecker, Alvin Chen
Contrastive Self-Supervised Learning for Spatio-Temporal Analysis of Lung Ultrasound Videos. ISBI (2023)
Kangni Liu, Shahin Hashemkhani, Jonathan Rubin, Rajkumar Kubendran
Neuromorphic Networks using Nonlinear Mixed-feedback Multi-timescale Bio-mimetic Neurons. ISCAS (2023)
Jonathan Rubin, Ramon Erkamp, Ragha Srinivasa Naidu, Anumod Odungatta Thodiyil, Alvin Chen
Attention Distillation for Detection Transformers: Application to Real-Time Video Object Detection in Ultrasound. ML4H@NeurIPS (2021)
Asif Rahman, Yale Chang, Jonathan Rubin
Interpretable Additive Recurrent Neural Networks For Multivariate Clinical Time Series. CoRR (2021)
Annamalai Natarajan, Gregory Boverman, Yale Chang, Corneliu Antonescu, Jonathan Rubin
Convolution-Free Waveform Transformers for Multi-Lead ECG Classification. CinC (2021)
Annamalai Natarajan, Gregory Boverman, Yale Chang, Corneliu Antonescu, Jonathan Rubin
Convolution-Free Waveform Transformers for Multi-Lead ECG Classification. CoRR (2021)
Annamalai Natarajan, Yale Chang, Sara Mariani, Asif Rahman, Gregory Boverman, Shruti Vij, Jonathan Rubin
A Wide and Deep Transformer Neural Network for 12-Lead ECG Classification. CinC (2020)
Yumin Liu, Claire Zhao, Jonathan Rubin
Uncertainty Quantification in Chest X-Ray Image Classification using Bayesian Deep Neural Networks. KDH@ECAI (2020)
Yale Chang, Jonathan Rubin, Gregory Boverman, Shruti Vij, Asif Rahman, Annamalai Natarajan, Saman Parvaneh
A Multi-Task Imputation and Classification Neural Architecture for Early Prediction of Sepsis from Multivariate Clinical Time Series. CinC (2019)
Jonathan Rubin, Sayed Mazdak Abulnaga
CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation. CoRR (2019)
Ruizhi Liao, Jonathan Rubin, Grace Lam, Seth J. Berkowitz, Sandeep Dalal, William Wells, Steven Horng, Polina Golland
Semi-supervised Learning for Quantification of Pulmonary Edema in Chest X-Ray Images. CoRR (2019)
Jonathan Rubin, Sayed Mazdak Abulnaga
CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation. ICHI (2019)
Jwala Dhamala, Emmanuel Azuh, Abdullah Al-Dujaili, Jonathan Rubin, Una-May O'Reilly
Multivariate Time-series Similarity Assessment via Unsupervised Representation Learning and Stratified Locality Sensitive Hashing: Application to Early Acute Hypotensive Episode Detection. CoRR (2018)
Sayed Mazdak Abulnaga, Jonathan Rubin
Ischemic Stroke Lesion Segmentation in CT Perfusion Scans using Pyramid Pooling and Focal Loss. CoRR (2018)
Jonathan Rubin, Cristhian Potes, Minnan Xu-Wilson, Junzi Dong, Asif Rahman, Hiep Nguyen, David Moromisato
An ensemble boosting model for predicting transfer to the pediatric intensive care unit. Int. J. Medical Informatics 112 (2018)
Saman Parvaneh, Jonathan Rubin, Ali Samadani, Gajendra Katuwal
Automatic Detection of Arousals during Sleep using Multiple Physiological Signals. CoRR (2018)
Saman Parvaneh, Jonathan Rubin, Ali Samadani, Gajendra Katuwal
Automatic Detection of Arousals During Sleep Using Multiple Physiological Signals. CinC (2018)
Saman Parvaneh, Jonathan Rubin
Electrocardiogram Monitoring and Interpretation: From Traditional Machine Learning to Deep Learning, and Their Combination. CinC (2018)
Sayed Mazdak Abulnaga, Jonathan Rubin
Ischemic Stroke Lesion Segmentation in CT Perfusion Scans Using Pyramid Pooling and Focal Loss. BrainLes@MICCAI (1) (2018)
Jonathan Rubin, Deepan Sanghavi, Claire Zhao, Kathy Lee, Ashequl Qadir, Minnan Xu-Wilson
Large Scale Automated Reading of Frontal and Lateral Chest X-Rays using Dual Convolutional Neural Networks. CoRR (2018)
Jonathan Rubin, Cristhian Potes, Minnan Xu-Wilson, Junzi Dong, Asif Rahman, Hiep Nguyen, David Moromisato
An Ensemble Boosting Model for Predicting Transfer to the Pediatric Intensive Care Unit. CoRR (2017)
Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan
Recognizing Abnormal Heart Sounds Using Deep Learning. KHD@IJCAI (2017)
Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan
Recognizing Abnormal Heart Sounds Using Deep Learning. CoRR (2017)
Jonathan Rubin, Saman Parvaneh, Asif Rahman, Bryan Conroy, Saeed Babaeizadeh
Densely Connected Convolutional Networks and Signal Quality Analysis to Detect Atrial Fibrillation Using Short Single-Lead ECG Recordings. CoRR (2017)
David Burstein, Jonathan Rubin
Sufficient Conditions for Graphicality of Bidegree Sequences. SIAM J. Discret. Math. 31 (1) (2017)
Saman Parvaneh, Jonathan Rubin, Asif Rahman, Bryan Conroy, Saeed Babaeizadeh
Densely Connected Convolutional Networks and Signal Quality Analysis to Detect Atrial Fibrillation Using Short Single-Lead ECG Recordings. CinC (2017)
Jonathan Rubin, Nachum Ulanovsky, Israel Nelken, Naftali Tishby
The Representation of Prediction Error in Auditory Cortex. PLoS Comput. Biol. 12 (8) (2016)
Jonathan Rubin, Rui Abreu, Shane Ahern, Hoda Eldardiry, Daniel G. Bobrow
Time, frequency & complexity analysis for recognizing panic states from physiologic time-series. PervasiveHealth (2016)
Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan
Classifying Heart Sound Recordings using Deep Convolutional Neural Networks and Mel-Frequency Cepstral Coefficients. CinC (2016)
Jonathan Rubin, Hoda Eldardiry, Rui Abreu, Shane Ahern, Honglu Du, Ashish Pattekar, Daniel G. Bobrow
Towards a mobile and wearable system for predicting panic attacks. UbiComp (2015)
Luis Cruz, Jonathan Rubin, Rui Abreu, Shane Ahern, Hoda Eldardiry, Daniel G. Bobrow
A wearable and mobile intervention delivery system for individuals with panic disorder. MUM (2015)
David Burstein, Jonathan Rubin
Sufficient Conditions for Graphicality of Bidegree Sequences. CoRR (2015)
David Burstein, Jonathan Rubin
Degree switching and partitioning for enumerating graphs to arbitrary orders of accuracy. CoRR (2015)
Nolan Bard, John Alexander Hawkin, Jonathan Rubin, Martin Zinkevich
The Annual Computer Poker Competition. AI Mag. 34 (2) (2013)
Jonathan Rubin, Ian D. Watson
Decision Generalisation from Game Logs in No Limit Texas Hold'em. IJCAI (2013)
Michael Silva, Silas McCroskey, Jonathan Rubin, Michael Youngblood, Ashwin Ram
Learning from Demonstration to Be a Good Team Member in a Role Playing Game. FLAIRS Conference (2013)
Ian D. Watson, Jonathan Rubin, Glen Robertson
SARTRE: a case-based poker web app. IE (2012)
Jonathan Rubin, Ian D. Watson
Opponent Type Adaptation for Case-Based Strategies in Adversarial Games. ICCBR (2012)
Jonathan Rubin, Ian D. Watson
Case-based strategies in computer poker. AI Commun. 25 (1) (2012)
Jonathan Rubin, Ian D. Watson
On Combining Decisions from Multiple Expert Imitators for Performance. IJCAI (2011)
Jonathan Rubin, Ian D. Watson
Computer poker: A review. Artif. Intell. 175 (5-6) (2011)
Jonathan Rubin, Ian D. Watson
Successful Performance via Decision Generalisation in No Limit Texas Hold'em. ICCBR (2011)
Jonathan Rubin, Ian D. Watson
Similarity-Based Retrieval and Solution Re-use Policies in the Game of Texas Hold'em. ICCBR (2010)
Jonathan Rubin, Ian D. Watson
A Memory-Based Approach to Two-Player Texas Hold'em. Australasian Conference on Artificial Intelligence (2009)
Ian D. Watson, Jonathan Rubin
Playing Texas Hold'em Poker Online Using Case-Based Reasoning. Int. J. Intell. Games Simul. 5 (2) (2009)
Ian D. Watson, Jonathan Rubin
CASPER: A Case-Based Poker-Bot. Australasian Conference on Artificial Intelligence (2008)
Ian D. Watson, Song Lee, Jonathan Rubin, Stefan Wender
Improving a case-based texas hold'em poker bot. CIG (2008)
Jonathan Rubin, Ian D. Watson
Investigating the Effectiveness of Applying Case-Based Reasoning to the Game of Texas Hold'em. FLAIRS Conference (2007)