Ricardo Henao - RankMe

181 papers A* 36A 11Misc 5Journal 87Unranked 41

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Automated calculation of spin-isospin branching rules for SU(4) irreps. Comput. Phys. Commun. S. Quintero, Ricardo Henao, J. P. Valencia
2026	J	`jnl`	GRAFT: Decoupling Ranking and Calibration for Survival Analysis. CoRR Mohammad Ashhad, Robert Hoehndorf, Ricardo Henao
2026	J	`jnl`	Labels have Human Values: Value Calibration of Subjective Tasks. CoRR Mohammed Fayiz Parappan, Ricardo Henao
2026	J	`jnl`	SIDEKICK: A Semantically Integrated Resource for Drug Effects, Indications, and Contraindications. CoRR Mohammad Ashhad, Olga Mashkova, Ricardo Henao, Robert Hoehndorf
2025	J	`jnl`	A robust and data-efficient deep learning model for cardiac assessment without segmentation. BMC Medical Imaging Conor M. Artman, Ricardo Henao
2025	J	`jnl`	Coupling Generative Modeling and an Autoencoder with the Causal Bridge. CoRR Ruolin Meng, Ming-Yu Chung, Dhanajit Brahma, Ricardo Henao, Lawrence Carin
2025	A	`conf`	Cross-Modal Imputation and Uncertainty Estimation for Spatial Transcriptomics. AISTATS Xiangyu Guo, Ricardo Henao
2025	J	`jnl`	Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models. Artif. Intell. Medicine Matthew Engelhard, Daniel Wojdyla, Haoyuan Wang, Michael J. Pencina, Ricardo Henao
2025	—	`conf`	Generating Accurate Synthetic Survival Data by Conditioning on Outcomes. MLHC Mohd Ashhad, Ricardo Henao
2025	A*	`conf`	Learning Subjective Label Distributions via Sociocultural Descriptors. EMNLP Mohammed Fayiz Parappan, Ricardo Henao
2025	A*	`conf`	Learning Survival Distributions with the Asymmetric Laplace Distribution. ICML Deming Sheng, Ricardo Henao
2025	J	`jnl`	Learning Survival Distributions with the Asymmetric Laplace Distribution. CoRR Deming Sheng, Ricardo Henao
2025	—	`conf`	Learning to Substitute Words with Model-based Score Ranking. NAACL (Long Papers) Hongye Liu, Ricardo Henao
2025	J	`jnl`	Learning to Substitute Words with Model-based Score Ranking. CoRR Hongye Liu, Ricardo Henao
2025	—	`conf`	Model Recycling Framework for Multi-Source Data-Free Supervised Transfer Learning. MLSP Sijia Wang, Ricardo Henao
2025	J	`jnl`	Model Recycling Framework for Multi-Source Data-Free Supervised Transfer Learning. CoRR Sijia Wang, Ricardo Henao
2025	A*	`conf`	On Understanding Attention-Based In-Context Learning for Categorical Data. ICML Aaron T. Wang, William Convertino, Xiang Cheng, Ricardo Henao, Lawrence Carin
2025	—	`conf`	Proactive Pseudo-Intervention: Pre-informed Contrastive Learning For Interpretable Vision Models. AAAI Bridge Program Dong Wang, Yuewei Yang, Liqun Chen, Zhe Gan, Ricardo Henao, Lawrence Carin
2025	—	`conf`	Toward Sustainable Continual Learning: Detection and Knowledge Repurposing for Reoccurring Tasks. MLSP Sijia Wang, Yoojin Choi, Junya Chen, Mostafa El-Khamy, Ricardo Henao
2024	J	`jnl`	A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis. J. Biomed. Informatics Wei A. Huang, Matthew Engelhard, Marika Coffman, Elliot D. Hill, Qin Weng, Abby Scheer, Gary Maslow, Ricardo Henao, Geraldine Dawson, Benjamin Alan Goldstein
2024	A	`conf`	Adaptive Discretization for Event PredicTion (ADEPT). AISTATS Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew Engelhard
2024	J	`jnl`	Conditioning on Time is All You Need for Synthetic Survival Data Generation. CoRR Mohd Ashhad, Ricardo Henao
2024	A*	`conf`	Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources. ICML Meng Xia, Jonathan Wilson, Benjamin Goldstein, Ricardo Henao
2024	J	`jnl`	Deep learning-driven pulmonary arteries and veins segmentation reveals demography-associated pulmonary vasculature anatomy. CoRR Yuetan Chu, Gongning Luo, Longxi Zhou, Shaodong Cao, Guolin Ma, Xianglin Meng, Juexiao Zhou, Changchun Yang, Dexuan Xie, Ricardo Henao, Xigang Xiao, Lianming Wu, Zhaowen Qiu, Xin Gao
2024	—	`conf`	Personalized Federated Learning for Text Classification with Gradient-Free Prompt Tuning. NAACL-HLT (Findings) Rui Wang, Tong Yu, Ruiyi Zhang, Sungchul Kim, Ryan A. Rossi, Handong Zhao, Junda Wu, Subrata Mitra, Lina Yao, Ricardo Henao
2024	J	`jnl`	Text Feature Adversarial Learning for Text Generation With Knowledge Transfer From GPT2. IEEE Trans. Neural Networks Learn. Syst. Hao Zhang, Yulai Cong, Zhengjue Wang, Lei Zhang, Miaoyun Zhao, Liqun Chen, Shijing Si, Ricardo Henao, Lawrence Carin
2024	J	`jnl`	Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance. J. Biomed. Informatics Chuan Hong, Molei Liu, Daniel Wojdyla, Jimmy Hickey, Michael J. Pencina, Ricardo Henao
2024	J	`jnl`	Transformer In-Context Learning for Categorical Data. CoRR Aaron T. Wang, Ricardo Henao, Lawrence Carin
2024	J	`jnl`	Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare. J. Am. Medical Informatics Assoc. Nicoleta J. Economou-Zavlanos, Sophia Bessias, Michael P. Cary, Armando Bedoya, Benjamin Goldstein, John Eric Jelovsek, Cara O'Brien, Nancy Walden, Matthew Elmore, Amanda B. Parrish, Scott Elengold, Kay S. Lytle, Suresh Balu, Michael E. Lipkin, Afreen Idris Shariff, Michael Gao, David Leverenz, Ricardo Henao, David Y. Ming, David M. Gallagher, Michael J. Pencina, Eric G. Poon
2023	A*	`conf`	An Effective Meaningful Way to Evaluate Survival Models. ICML Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner
2023	J	`jnl`	An Effective Meaningful Way to Evaluate Survival Models. CoRR Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner
2023	J	`jnl`	Calibration and Uncertainty in Neural Time-to-Event Modeling. IEEE Trans. Neural Networks Learn. Syst. Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Irfan Khan, Karen Chandross, Michael J. Pencina, Lawrence Carin, Ricardo Henao
2023	J	`jnl`	Enhancing early autism prediction based on electronic records using clinical narratives. J. Biomed. Informatics Junya Chen, Matthew Engelhard, Ricardo Henao, Samuel Berchuck, Brian Eichner, Eliana M. Perrin, Guillermo Sapiro, Geraldine Dawson
2023	A	`conf`	Estimating Total Correlation with Mutual Information Estimators. AISTATS Ke Bai, Pengyu Cheng, Weituo Hao, Ricardo Henao, Larry Carin
2023	—	`conf`	Federated Domain Adaptation for Named Entity Recognition via Distilling with Heterogeneous Tag Sets. ACL (Findings) Rui Wang, Tong Yu, Junda Wu, Handong Zhao, Sungchul Kim, Ruiyi Zhang, Subrata Mitra, Ricardo Henao
2023	A*	`conf`	Few-Shot Composition Learning for Image Retrieval with Prompt Tuning. AAAI Junda Wu, Rui Wang, Handong Zhao, Ruiyi Zhang, Chaochao Lu, Shuai Li, Ricardo Henao
2023	—	`conf`	Hawkes Process with Flexible Triggering Kernels. MLHC Yamac Alican Isik, Paidamoyo Chapfuwa, Connor Davis, Ricardo Henao
2023	J	`jnl`	Improving Event Time Prediction by Learning to Partition the Event Time Space. CoRR Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew M. Engelhard
2023	A*	`conf`	InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. NeurIPS Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao
2023	J	`jnl`	InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. CoRR Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao
2023	J	`jnl`	Learning Hierarchical Document Graphs From Multilevel Sentence Relations. IEEE Trans. Neural Networks Learn. Syst. Hao Zhang, Chaojie Wang, Zhengjue Wang, Zhibin Duan, Bo Chen, Mingyuan Zhou, Ricardo Henao, Lawrence Carin
2023	A*	`conf`	Mitigating Test-Time Bias for Fair Image Retrieval. NeurIPS Fanjie Kong, Shuai Yuan, Weituo Hao, Ricardo Henao
2023	J	`jnl`	Mitigating Test-Time Bias for Fair Image Retrieval. CoRR Fanjie Kong, Shuai Yuan, Weituo Hao, Ricardo Henao
2023	A*	`conf`	Neural Insights for Digital Marketing Content Design. KDD Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti
2023	J	`jnl`	Neural Insights for Digital Marketing Content Design. CoRR Fanjie Kong, Yuan Li, Tanner Fiez, Shreya Chakrabarti, Ricardo Henao, Houssam Nassif
2023	J	`jnl`	Open World Classification with Adaptive Negative Samples. CoRR Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin
2023	A	`conf`	Pushing the Efficiency Limit Using Structured Sparse Convolutions. WACV Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin
2023	J	`jnl`	Reliable Active Learning via Influence Functions. Trans. Mach. Learn. Res. Meng Xia, Ricardo Henao
2023	A	`conf`	Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling. AISTATS Rui Wang, Pengyu Cheng, Ricardo Henao
2023	J	`jnl`	Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling. CoRR Rui Wang, Pengyu Cheng, Ricardo Henao
2022	J	`jnl`	Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations. CoRR Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao
2022	A	`conf`	Capturing actionable dynamics with structured latent ordinary differential equations. UAI Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao
2022	J	`jnl`	Collaborative Anomaly Detection. CoRR Ke Bai, Aonan Zhang, Zhizhong Li, Ricardo Henao, Chong Wang, Lawrence Carin
2022	—	`conf`	Context-aware Information-theoretic Causal De-biasing for Interactive Sequence Labeling. EMNLP (Findings) Junda Wu, Rui Wang, Tong Yu, Ruiyi Zhang, Handong Zhao, Shuai Li, Ricardo Henao, Ani Nenkova
2022	A	`conf`	Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data. AISTATS Matthew Engelhard, Ricardo Henao
2022	A*	`conf`	Efficient Classification of Very Large Images with Tiny Objects. CVPR Fanjie Kong, Ricardo Henao
2022	—	`conf`	Few-Shot Class-Incremental Learning for Named Entity Recognition. ACL (1) Rui Wang, Tong Yu, Handong Zhao, Sungchul Kim, Subrata Mitra, Ruiyi Zhang, Ricardo Henao
2022	J	`jnl`	Flexible Triggering Kernels for Hawkes Process Modeling. CoRR Yamac Alican Isik, Connor Davis, Paidamoyo Chapfuwa, Ricardo Henao
2022	A*	`conf`	Gradient Importance Learning for Incomplete Observations. ICLR Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic
2022	A*	`conf`	Open World Classification with Adaptive Negative Samples. EMNLP Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin
2022	J	`jnl`	Predicting in-hospital length of stay: a two-stage modeling approach to account for highly skewed data. BMC Medical Informatics Decis. Mak. Zhenhui Xu, Congwen Zhao, Charles D. Scales, Ricardo Henao, Benjamin Alan Goldstein
2022	J	`jnl`	Pushing the Efficiency Limit Using Structured Sparse Convolutions. CoRR Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin
2022	J	`jnl`	TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile. PLoS Comput. Biol. Tianqi Yang, Ricardo Henao
2022	J	`jnl`	Toward Sustainable Continual Learning: Detection and Knowledge Repurposing of Similar Tasks. CoRR Sijia Wang, Yoojin Choi, Junya Chen, Mostafa El-Khamy, Ricardo Henao
2022	Misc	`conf`	Wasserstein Cross-Lingual Alignment For Named Entity Recognition. ICASSP Rui Wang, Ricardo Henao
2022	J	`jnl`	Wasserstein Uncertainty Estimation for Adversarial Domain Matching. Frontiers Big Data Rui Wang, Ruiyi Zhang, Ricardo Henao
2021	J	`jnl`	Adaptive Multi-Channel Event Segmentation and Feature Extraction for Monitoring Health Outcomes. IEEE Trans. Biomed. Eng. Xichen She, Yaya Zhai, Ricardo Henao, Christopher W. Woods, Christopher Chiu, Geoffrey S. Ginsburg, Peter X. K. Song, Alfred O. Hero III
2021	—	`conf`	Affinitention nets: kernel perspective on attention architectures for set classification with applications to medical text and images. CHIL David Dov, Serge Assaad, Shijing Si, Rui Wang, Hongteng Xu, Shahar Ziv Kovalsky, Jonathan Bell, Danielle Elliott Range, Jonathan Cohen, Ricardo Henao, Lawrence Carin
2021	A	`conf`	Counterfactual Representation Learning with Balancing Weights. AISTATS Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin
2021	J	`jnl`	Efficient Classification of Very Large Images with Tiny Objects. CoRR Fanjie Kong, Ricardo Henao
2021	—	`conf`	Enabling counterfactual survival analysis with balanced representations. CHIL Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng, Michael J. Pencina, Lawrence Carin, Ricardo Henao
2021	J	`jnl`	Imputation-Free Learning from Incomplete Observations. CoRR Qitong Gao, Dong Wang, Joshua D. Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic
2021	J	`jnl`	Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes. Medical Image Anal. Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin
2021	J	`jnl`	Malignancy Prediction and Lesion Identification from Clinical Dermatological Images. CoRR Meng Xia, Meenal K. Kheterpal, Samantha C. Wong, Christine Park, William Ratliff, Lawrence Carin, Ricardo Henao
2021	J	`jnl`	Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification. CoRR Fanjie Kong, Xiao-Yang Liu, Ricardo Henao
2021	—	`conf`	SpanPredict: Extraction of Predictive Document Spans with Neural Attention. NAACL-HLT Vivek Subramanian, Matthew Engelhard, Samuel Berchuck, Liqun Chen, Ricardo Henao, Lawrence Carin
2021	A*	`conf`	Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer. NeurIPS Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao
2021	—	`conf`	Unsupervised Paraphrasing Consistency Training for Low Resource Named Entity Recognition. EMNLP (1) Rui Wang, Ricardo Henao
2021	A*	`conf`	Variational Disentanglement for Rare Event Modeling. AAAI Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao
2021	A*	`conf`	Wasserstein Contrastive Representation Distillation. CVPR Liqun Chen, Dong Wang, Zhe Gan, Jingjing Liu, Ricardo Henao, Lawrence Carin
2021	J	`jnl`	Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images. Medical Image Anal. David Dov, Shahar Z. Kovalsky, Serge Assaad, Jonathan Cohen, Danielle Elliott Range, Avani A. Pendse, Ricardo Henao, Lawrence Carin
2020	A	`conf`	Advancing weakly supervised cross-domain alignment with optimal transport. BMVC Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin
2020	J	`jnl`	Counterfactual Representation Learning with Balancing Weights. CoRR Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin
2020	—	`conf`	Integrating Task Specific Information into Pretrained Language Models for Low Resource Fine Tuning. EMNLP (Findings) Rui Wang, Shijing Si, Guoyin Wang, Lei Zhang, Lawrence Carin, Ricardo Henao
2020	A*	`conf`	Learning Autoencoders with Relational Regularization. ICML Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin
2020	J	`jnl`	Learning Autoencoders with Relational Regularization. CoRR Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin
2020	J	`jnl`	Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes. CoRR Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin
2020	—	`conf`	Neural Conditional Event Time Models. MLHC Matthew Engelhard, Samuel Berchuck, Joshua D'Arcy, Ricardo Henao
2020	J	`jnl`	Neural Conditional Event Time Models. CoRR Matthew Engelhard, Samuel Berchuck, Joshua D'Arcy, Ricardo Henao
2020	J	`jnl`	Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models. CoRR Dong Wang, Yuewei Yang, Chenyang Tao, Fanjie Kong, Ricardo Henao, Lawrence Carin
2020	A*	`conf`	Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning. AAAI Liqun Chen, Ke Bai, Chenyang Tao, Yizhe Zhang, Guoyin Wang, Wenlin Wang, Ricardo Henao, Lawrence Carin
2020	J	`jnl`	Students Need More Attention: BERT-based AttentionModel for Small Data with Application to AutomaticPatient Message Triage. CoRR Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Ricardo Henao, Lawrence Carin
2020	J	`jnl`	Supercharging Imbalanced Data Learning With Causal Representation Transfer. CoRR Junya Chen, Zidi Xiu, Benjamin Alan Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao
2020	J	`jnl`	Survival Analysis meets Counterfactual Inference. CoRR Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng, Michael J. Pencina, Lawrence Carin, Ricardo Henao
2020	J	`jnl`	Survival Cluster Analysis. CoRR Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao
2020	—	`conf`	Survival cluster analysis. CHIL Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao
2020	J	`jnl`	Variational Disentanglement for Rare Event Modeling. CoRR Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao
2020	J	`jnl`	Variational Learning of Individual Survival Distributions. CoRR Zidi Xiu, Chenyang Tao, Ricardo Henao
2020	—	`conf`	Variational learning of individual survival distributions. CHIL Zidi Xiu, Chenyang Tao, Ricardo Henao
2020	J	`jnl`	Wasserstein Contrastive Representation Distillation. CoRR Liqun Chen, Zhe Gan, Dong Wang, Jingjing Liu, Ricardo Henao, Lawrence Carin
2020	J	`jnl`	Weakly supervised cross-domain alignment with optimal transport. CoRR Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin
2019	J	`jnl`	A Deep-Learning Algorithm for Thyroid Malignancy Prediction From Whole Slide Cytopathology Images. CoRR David Dov, Shahar Ziv Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin
2019	—	`conf`	Classifying abnormalities in computed tomography radiology reports with rule-based and natural language processing models. Computer-Aided Diagnosis Songyue Han, James Tian, Mark Kelly, Vignesh Selvakumaran, Ricardo Henao, Geoffrey D. Rubin, Joseph Y. Lo
2019	—	`conf`	Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports. Computer-Aided Diagnosis Matias Benitez, James Tian, Mark Kelly, Vignesh Selvakumaran, Matthew Phelan, Maciej A. Mazurowski, Joseph Y. Lo, Geoffrey D. Rubin, Ricardo Henao
2019	A*	`conf`	Communication-Efficient Stochastic Gradient MCMC for Neural Networks. AAAI Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin
2019	J	`jnl`	Discriminative Clustering for Robust Unsupervised Domain Adaptation. CoRR Rui Wang, Guoyin Wang, Ricardo Henao
2019	A*	`conf`	Improving Textual Network Learning with Variational Homophilic Embeddings. NeurIPS Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin
2019	J	`jnl`	Improving Textual Network Learning with Variational Homophilic Embeddings. CoRR Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin
2019	A*	`conf`	Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. NeurIPS Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin
2019	J	`jnl`	Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. CoRR Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin
2019	J	`jnl`	Straight-Through Estimator as Projected Wasserstein Gradient Flow. CoRR Pengyu Cheng, Chang Liu, Chunyuan Li, Dinghan Shen, Ricardo Henao, Lawrence Carin
2019	J	`jnl`	Survival Function Matching for Calibrated Time-to-Event Predictions. CoRR Paidamoyo Chapfuwa, Chenyang Tao, Lawrence Carin, Ricardo Henao
2019	—	`conf`	Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. MLHC David Dov, Shahar Z. Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin
2019	J	`jnl`	Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. CoRR David Dov, Shahar Ziv Kovalsky, Jonathan Cohen, Danielle Range, Ricardo Henao, Lawrence Carin
2018	A*	`conf`	Adversarial Time-to-Event Modeling. ICML Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao
2018	J	`jnl`	Adversarial Time-to-Event Modeling. CoRR Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao
2018	—	`conf`	Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. ACL (1) Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin
2018	J	`jnl`	Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. CoRR Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin
2018	A*	`conf`	Chi-square Generative Adversarial Network. ICML Chenyang Tao, Liqun Chen, Ricardo Henao, Jianfeng Feng, Lawrence Carin
2018	A*	`conf`	Deconvolutional Latent-Variable Model for Text Sequence Matching. AAAI Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin
2018	A*	`conf`	Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. EMNLP Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin
2018	J	`jnl`	Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. CoRR Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin
2018	—	`conf`	Joint Embedding of Words and Labels for Text Classification. ACL (1) Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin
2018	J	`jnl`	Joint Embedding of Words and Labels for Text Classification. CoRR Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin
2018	A*	`conf`	JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. ICML Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin
2018	J	`jnl`	JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. CoRR Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin
2018	—	`conf`	Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. MLHC Xinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin
2018	J	`jnl`	Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. CoRR Xinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin
2018	—	`conf`	NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. ACL (1) Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa, Wenlin Wang, Guoyin Wang, Ricardo Henao, Lawrence Carin
2018	J	`jnl`	NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. CoRR Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa, Wenlin Wang, Guoyin Wang, Lawrence Carin, Ricardo Henao
2018	Misc	`conf`	The Duke Health Data Science Internship Program: Integrating the Educational Mission into Real-World Research. AMIA Shelley A. Rusincovitch, Lisa Wruck, Ricardo Henao, Larisa Rodgers, Allison Dunning, Peter Merrill, Hillary Mulder, Robert Overton, Matthew Phelan, Erich Huang, Lawrence Carin, Michael J. Pencina
2018	A*	`conf`	Variational Inference and Model Selection with Generalized Evidence Bounds. ICML Liqun Chen, Chenyang Tao, Ruiyi Zhang, Ricardo Henao, Lawrence Carin
2017	—	`conf`	ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching. NIPS Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin
2017	A*	`conf`	Adversarial Feature Matching for Text Generation. ICML Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin
2017	J	`jnl`	Adversarial Feature Matching for Text Generation. CoRR Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin
2017	—	`conf`	Adversarial Symmetric Variational Autoencoder. NIPS Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin
2017	J	`jnl`	Adversarial Symmetric Variational Autoencoder. CoRR Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin
2017	J	`jnl`	Deconvolutional Latent-Variable Model for Text Sequence Matching. CoRR Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin
2017	—	`conf`	Deconvolutional Paragraph Representation Learning. NIPS Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin
2017	J	`jnl`	Deconvolutional Paragraph Representation Learning. CoRR Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin
2017	J	`jnl`	Gaussian process based independent analysis for temporal source separation in fMRI. NeuroImage Ditte Høvenhoff Hald, Ricardo Henao, Ole Winther
2017	Misc	`conf`	Guiding Principles for the Duke Connected Care Predictive Modeling Pilot. AMIA Eugenie Komives, Shelley A. Rusincovitch, John Paat, Lawrence Carin, Daniel Costello, Michael Gao, Bradley G. Hammill, Ricardo Henao, Nigel B. Neely, Ursula Rogers, Devdutta Sangvai, Mary Schilder, Erich Huang
2017	A*	`conf`	Learning Generic Sentence Representations Using Convolutional Neural Networks. EMNLP Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin
2017	Misc	`conf`	Rationale and Design for the Duke Connected Care Predictive Modeling Pilot with a Medicare Shared Savings Program Population. AMIA Shelley A. Rusincovitch, Ricardo Henao, Michael Gao, Lawrence Carin, Ursula Rogers, Nigel B. Neely, Mary Schilder, Daniel Costello, Eugenie Komives, Erich Huang
2017	J	`jnl`	Stein Variational Autoencoder. CoRR Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin
2017	A*	`conf`	Stochastic Gradient Monomial Gamma Sampler. ICML Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin
2017	J	`jnl`	Stochastic Gradient Monomial Gamma Sampler. CoRR Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin
2017	J	`jnl`	Towards Understanding Adversarial Learning for Joint Distribution Matching. CoRR Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin
2017	—	`conf`	VAE Learning via Stein Variational Gradient Descent. NIPS Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin
2016	A*	`conf`	Bayesian Dictionary Learning with Gaussian Processes and Sigmoid Belief Networks. IJCAI Yizhe Zhang, Ricardo Henao, Chunyuan Li, Lawrence Carin
2016	A*	`conf`	Dynamic Poisson Factor Analysis. ICDM Yizhe Zhang, Yue Zhao, Lawrence David, Ricardo Henao, Lawrence Carin
2016	J	`jnl`	Electronic Health Record Analysis via Deep Poisson Factor Models. J. Mach. Learn. Res. Ricardo Henao, James Lu, Joseph E. Lucas, Jeffrey M. Ferranti, Lawrence Carin
2016	—	`ch.`	Inference of gene networks associated with the host response to infectious disease. Big Data over Networks Zhe Gan, Xin Yuan, Ricardo Henao, Ephraim L. Tsalik, Lawrence Carin
2016	—	`conf`	Laplacian Hamiltonian Monte Carlo. ECML/PKDD (1) Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin
2016	A	`conf`	Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization. AISTATS Zhao Song, Ricardo Henao, David E. Carlson, Lawrence Carin
2016	A*	`conf`	Learning a Hybrid Architecture for Sequence Regression and Annotation. AAAI Yizhe Zhang, Ricardo Henao, Lawrence Carin, Jianling Zhong, Alexander J. Hartemink
2016	—	`conf`	Towards Unifying Hamiltonian Monte Carlo and Slice Sampling. NIPS Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin
2016	A*	`conf`	Triply Stochastic Variational Inference for Non-linear Beta Process Factor Analysis. ICDM Kai Fan, Yizhe Zhang, Ricardo Henao, Katherine A. Heller
2016	J	`jnl`	Unsupervised Learning of Sentence Representations using Convolutional Neural Networks. CoRR Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin
2016	—	`conf`	Variational Autoencoder for Deep Learning of Images, Labels and Captions. NIPS Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin
2016	J	`jnl`	Variational Autoencoder for Deep Learning of Images, Labels and Captions. CoRR Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin
2015	A*	`conf`	A Multitask Point Process Predictive Model. ICML Wenzhao Lian, Ricardo Henao, Vinayak A. Rao, Joseph E. Lucas, Lawrence Carin
2015	—	`conf`	Deep Poisson Factor Modeling. NIPS Ricardo Henao, Zhe Gan, James Lu, Lawrence Carin
2015	—	`conf`	Deep Temporal Sigmoid Belief Networks for Sequence Modeling. NIPS Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson, Lawrence Carin
2015	J	`jnl`	Deep Temporal Sigmoid Belief Networks for Sequence Modeling. CoRR Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson, Lawrence Carin
2015	—	`conf`	Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings. NIPS Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin
2015	A	`conf`	Learning Deep Sigmoid Belief Networks with Data Augmentation. AISTATS Zhe Gan, Ricardo Henao, David E. Carlson, Lawrence Carin
2015	A*	`conf`	Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood. ICML Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin
2015	A*	`conf`	Scalable Deep Poisson Factor Analysis for Topic Modeling. ICML Zhe Gan, Changyou Chen, Ricardo Henao, David E. Carlson, Lawrence Carin
2014	—	`conf`	Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling. NIPS Ricardo Henao, Xin Yuan, Lawrence Carin
2013	J	`jnl`	A flexible statistical model for alignment of label-free proteomics data - incorporating ion mobility and product ion information. BMC Bioinform. Ashlee M. Benjamin, J. Will Thompson, Erik J. Soderblom, Scott J. Geromanos, Ricardo Henao, Virginia B. Kraus, M. Arthur Moseley, Joseph E. Lucas
2013	Misc	`conf`	Patient Clustering with Uncoded Text in Electronic Medical Records. AMIA Ricardo Henao, Jared Murray, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas
2012	—	`conf`	Hierarchical factor modeling of proteomics data. ICCABS Ricardo Henao, J. Will Thompson, M. Arthur Moseley, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas
2012	J	`jnl`	High Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections. IEEE Signal Process. Mag. Lawrence Carin, Alfred O. Hero III, Joseph E. Lucas, David B. Dunson, Minhua Chen, Ricardo Henao, Arnau Tibau Puig, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg
2012	J	`jnl`	Predictive active set selection methods for Gaussian processes. Neurocomputing Ricardo Henao, Ole Winther
2011	J	`jnl`	Sparse Linear Identifiable Multivariate Modeling. J. Mach. Learn. Res. Ricardo Henao, Ole Winther
2010	J	`jnl`	Semi-Supervised Kernel PCA CoRR Christian Walder, Ricardo Henao, Morten Mørup, Lars Kai Hansen
2009	—	`conf`	Bayesian Sparse Factor Models and DAGs Inference and Comparison. NIPS Ricardo Henao, Ole Winther
2006	—	`conf`	Kernel Principal Component Analysis through Time for Voice Disorder Classification. EMBC Mauricio A. Álvarez, Ricardo Henao, Germán Castellanos-Domínguez, Juan Ignacio Godino-Llorente, Álvaro Ángel Orozco
2006	—	`conf`	Probabilistic Kernel Principal Component Analysis Through Time. ICONIP (1) Mauricio A. Álvarez, Ricardo Henao
2004	—	`conf`	Active learning on the classification of voice pathologies. Odyssey Carlos Lino Rengifo, Diego Andrés Alvarez, Ricardo Henao, Germán Castellanos, Jorge Eduardo Hurtado