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ORCIDRicardo Henao
Person information
- affiliation: Duke University, School of Medicine, Department of Biostatistics and Bioinformatics, Durham, NC, USA
- affiliation: King Abdullah University of Science and Technology (KAUST), Saudi Arabia
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2020 – today
- 2025
[j22]Matthew Engelhard, Daniel Wojdyla, Haoyuan Wang, Michael J. Pencina, Ricardo Henao:
Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models. Artif. Intell. Medicine 164: 103130 (2025)- [j21]Conor M. Artman, Ricardo Henao:
A robust and data-efficient deep learning model for cardiac assessment without segmentation. BMC Medical Imaging 25(1): 423 (2025) - [c90]Xiangyu Guo, Ricardo Henao:
Cross-Modal Imputation and Uncertainty Estimation for Spatial Transcriptomics. AISTATS 2025: 4375-4383 - [c89]Deming Sheng, Ricardo Henao:
Learning Survival Distributions with the Asymmetric Laplace Distribution. ICML 2025 - [c88]Aaron T. Wang, William Convertino, Xiang Cheng, Ricardo Henao, Lawrence Carin:
On Understanding Attention-Based In-Context Learning for Categorical Data. ICML 2025 - [c87]Sijia Wang, Yoojin Choi, Junya Chen, Mostafa El-Khamy, Ricardo Henao:
Toward Sustainable Continual Learning: Detection and Knowledge Repurposing for Reoccurring Tasks. MLSP 2025: 1-6 - [c86]Sijia Wang, Ricardo Henao:
Model Recycling Framework for Multi-Source Data-Free Supervised Transfer Learning. MLSP 2025: 1-6 - [c85]Hongye Liu, Ricardo Henao:
Learning to Substitute Words with Model-based Score Ranking. NAACL (Long Papers) 2025: 11551-11565 - [i61]Hongye Liu, Ricardo Henao:
Learning to Substitute Words with Model-based Score Ranking. CoRR abs/2502.05933 (2025) - [i60]Deming Sheng, Ricardo Henao:
Learning Survival Distributions with the Asymmetric Laplace Distribution. CoRR abs/2505.03712 (2025) - [i59]Sijia Wang, Ricardo Henao:
Model Recycling Framework for Multi-Source Data-Free Supervised Transfer Learning. CoRR abs/2508.02039 (2025) - [i58]Ruolin Meng, Ming-Yu Chung, Dhanajit Brahma, Ricardo Henao, Lawrence Carin:
Coupling Generative Modeling and an Autoencoder with the Causal Bridge. CoRR abs/2509.25599 (2025) - 2024
- [j20]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:
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. 31(3): 705-713 (2024) - [j19]Chuan Hong, Molei Liu, Daniel Wojdyla, Jimmy Hickey, Michael J. Pencina, Ricardo Henao:
Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance. J. Biomed. Informatics 149: 104532 (2024) - [j18]Wei A. Huang, Matthew Engelhard, Marika Coffman, Elliot D. Hill, Qin Weng, Abby Scheer, Gary Maslow, Ricardo Henao, Geraldine Dawson, Benjamin Alan Goldstein:
A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis. J. Biomed. Informatics 157: 104711 (2024) - [j17]Hao Zhang, Yulai Cong, Zhengjue Wang, Lei Zhang, Miaoyun Zhao, Liqun Chen, Shijing Si, Ricardo Henao, Lawrence Carin:
Text Feature Adversarial Learning for Text Generation With Knowledge Transfer From GPT2. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6558-6569 (2024) - [c84]Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew Engelhard:
Adaptive Discretization for Event PredicTion (ADEPT). AISTATS 2024: 1351-1359 - [c83]Meng Xia, Jonathan Wilson, Benjamin Goldstein, Ricardo Henao:
Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources. ICML 2024 - [c82]Rui Wang, Tong Yu, Ruiyi Zhang, Sungchul Kim, Ryan A. Rossi, Handong Zhao, Junda Wu, Subrata Mitra, Lina Yao, Ricardo Henao:
Personalized Federated Learning for Text Classification with Gradient-Free Prompt Tuning. NAACL-HLT (Findings) 2024: 4597-4612 - [i57]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:
Deep learning-driven pulmonary arteries and veins segmentation reveals demography-associated pulmonary vasculature anatomy. CoRR abs/2404.07671 (2024) - [i56]Aaron T. Wang, Ricardo Henao, Lawrence Carin:
Transformer In-Context Learning for Categorical Data. CoRR abs/2405.17248 (2024) - [i55]Mohd Ashhad, Ricardo Henao:
Conditioning on Time is All You Need for Synthetic Survival Data Generation. CoRR abs/2405.17333 (2024) - 2023
- [j16]Junya Chen, Matthew Engelhard, Ricardo Henao, Samuel Berchuck, Brian Eichner, Eliana M. Perrin, Guillermo Sapiro, Geraldine Dawson:
Enhancing early autism prediction based on electronic records using clinical narratives. J. Biomed. Informatics 144: 104390 (2023) - [j15]Meng Xia, Ricardo Henao:
Reliable Active Learning via Influence Functions. Trans. Mach. Learn. Res. 2023 (2023) - [j14]Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Irfan Khan, Karen Chandross, Michael J. Pencina, Lawrence Carin, Ricardo Henao:
Calibration and Uncertainty in Neural Time-to-Event Modeling. IEEE Trans. Neural Networks Learn. Syst. 34(4): 1666-1680 (2023) - [j13]Hao Zhang, Chaojie Wang, Zhengjue Wang, Zhibin Duan, Bo Chen, Mingyuan Zhou, Ricardo Henao, Lawrence Carin:
Learning Hierarchical Document Graphs From Multilevel Sentence Relations. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4273-4285 (2023) - [c81]Junda Wu, Rui Wang, Handong Zhao, Ruiyi Zhang, Chaochao Lu, Shuai Li, Ricardo Henao:
Few-Shot Composition Learning for Image Retrieval with Prompt Tuning. AAAI 2023: 4729-4737 - [c80]Rui Wang, Tong Yu, Junda Wu, Handong Zhao, Sungchul Kim, Ruiyi Zhang, Subrata Mitra, Ricardo Henao:
Federated Domain Adaptation for Named Entity Recognition via Distilling with Heterogeneous Tag Sets. ACL (Findings) 2023: 7449-7463 - [c79]Ke Bai, Pengyu Cheng, Weituo Hao, Ricardo Henao, Larry Carin:
Estimating Total Correlation with Mutual Information Estimators. AISTATS 2023: 2147-2164 - [c78]Rui Wang, Pengyu Cheng, Ricardo Henao:
Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling. AISTATS 2023: 4473-4485 - [c77]Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner:
An Effective Meaningful Way to Evaluate Survival Models. ICML 2023: 28244-28276 - [c76]Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti:
Neural Insights for Digital Marketing Content Design. KDD 2023: 4320-4332 - [c75]Yamac Alican Isik, Paidamoyo Chapfuwa, Connor Davis, Ricardo Henao:
Hawkes Process with Flexible Triggering Kernels. MLHC 2023: 308-320 - [c74]Fanjie Kong, Shuai Yuan, Weituo Hao, Ricardo Henao:
Mitigating Test-Time Bias for Fair Image Retrieval. NeurIPS 2023 - [c73]Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao:
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. NeurIPS 2023 - [c72]Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin:
Pushing the Efficiency Limit Using Structured Sparse Convolutions. WACV 2023: 6492-6502 - [i54]Fanjie Kong, Yuan Li, Tanner Fiez, Shreya Chakrabarti, Ricardo Henao, Houssam Nassif:
Neural Insights for Digital Marketing Content Design. CoRR abs/2302.01416 (2023) - [i53]Rui Wang, Pengyu Cheng, Ricardo Henao:
Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling. CoRR abs/2302.13136 (2023) - [i52]Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin:
Open World Classification with Adaptive Negative Samples. CoRR abs/2303.05581 (2023) - [i51]Fanjie Kong, Shuai Yuan, Weituo Hao, Ricardo Henao:
Mitigating Test-Time Bias for Fair Image Retrieval. CoRR abs/2305.19329 (2023) - [i50]Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner:
An Effective Meaningful Way to Evaluate Survival Models. CoRR abs/2306.01196 (2023) - [i49]Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao:
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. CoRR abs/2306.04933 (2023) - [i48]Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew M. Engelhard:
Improving Event Time Prediction by Learning to Partition the Event Time Space. CoRR abs/2310.15853 (2023) - 2022
- [j12]Rui Wang, Ruiyi Zhang, Ricardo Henao:
Wasserstein Uncertainty Estimation for Adversarial Domain Matching. Frontiers Big Data 5: 878716 (2022) - [j11]Zhenhui Xu, Congwen Zhao, Charles D. Scales, Ricardo Henao, Benjamin Alan Goldstein:
Predicting in-hospital length of stay: a two-stage modeling approach to account for highly skewed data. BMC Medical Informatics Decis. Mak. 22(1): 110 (2022) - [j10]Tianqi Yang, Ricardo Henao:
TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile. PLoS Comput. Biol. 18(9): 1009921 (2022) - [c71]Rui Wang, Tong Yu, Handong Zhao, Sungchul Kim, Subrata Mitra, Ruiyi Zhang, Ricardo Henao:
Few-Shot Class-Incremental Learning for Named Entity Recognition. ACL (1) 2022: 571-582 - [c70]Matthew Engelhard, Ricardo Henao:
Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data. AISTATS 2022: 9571-9581 - [c69]Fanjie Kong, Ricardo Henao:
Efficient Classification of Very Large Images with Tiny Objects. CVPR 2022: 2374-2384 - [c68]Junda Wu, Rui Wang, Tong Yu, Ruiyi Zhang, Handong Zhao, Shuai Li, Ricardo Henao, Ani Nenkova:
Context-aware Information-theoretic Causal De-biasing for Interactive Sequence Labeling. EMNLP (Findings) 2022: 3436-3448 - [c67]Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin:
Open World Classification with Adaptive Negative Samples. EMNLP 2022: 4378-4392 - [c66]Rui Wang, Ricardo Henao:
Wasserstein Cross-Lingual Alignment For Named Entity Recognition. ICASSP 2022: 8342-8346 - [c65]Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic:
Gradient Importance Learning for Incomplete Observations. ICLR 2022 - [c64]Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao:
Capturing actionable dynamics with structured latent ordinary differential equations. UAI 2022: 286-295 - [i47]Yamac Alican Isik, Connor Davis, Paidamoyo Chapfuwa, Ricardo Henao:
Flexible Triggering Kernels for Hawkes Process Modeling. CoRR abs/2202.01869 (2022) - [i46]Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao:
Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations. CoRR abs/2202.12932 (2022) - [i45]Ke Bai, Aonan Zhang, Zhizhong Li, Ricardo Henao, Chong Wang, Lawrence Carin:
Collaborative Anomaly Detection. CoRR abs/2209.09923 (2022) - [i44]Sijia Wang, Yoojin Choi, Junya Chen, Mostafa El-Khamy, Ricardo Henao:
Toward Sustainable Continual Learning: Detection and Knowledge Repurposing of Similar Tasks. CoRR abs/2210.05751 (2022) - [i43]Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin:
Pushing the Efficiency Limit Using Structured Sparse Convolutions. CoRR abs/2210.12818 (2022) - 2021
- [j9]David Dov, Shahar Z. Kovalsky, Serge Assaad, Jonathan Cohen, Danielle Elliott Range, Avani A. Pendse, Ricardo Henao, Lawrence Carin:
Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images. Medical Image Anal. 67: 101814 (2021) - [j8]Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin:
Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes. Medical Image Anal. 67: 101857 (2021) - [j7]Xichen She, Yaya Zhai, Ricardo Henao, Christopher W. Woods, Christopher Chiu, Geoffrey S. Ginsburg, Peter X. K. Song, Alfred O. Hero III:
Adaptive Multi-Channel Event Segmentation and Feature Extraction for Monitoring Health Outcomes. IEEE Trans. Biomed. Eng. 68(8): 2377-2388 (2021) - [c63]Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao:
Variational Disentanglement for Rare Event Modeling. AAAI 2021: 10469-10477 - [c62]Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin:
Counterfactual Representation Learning with Balancing Weights. AISTATS 2021: 1972-1980 - [c61]David Dov, Serge Assaad, Shijing Si, Rui Wang, Hongteng Xu, Shahar Ziv Kovalsky, Jonathan Bell, Danielle Elliott Range, Jonathan Cohen, Ricardo Henao, Lawrence Carin:
Affinitention nets: kernel perspective on attention architectures for set classification with applications to medical text and images. CHIL 2021: 14-24 - [c60]Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng, Michael J. Pencina, Lawrence Carin, Ricardo Henao:
Enabling counterfactual survival analysis with balanced representations. CHIL 2021: 133-145 - [c59]Liqun Chen, Dong Wang, Zhe Gan, Jingjing Liu, Ricardo Henao, Lawrence Carin:
Wasserstein Contrastive Representation Distillation. CVPR 2021: 16296-16305 - [c58]Rui Wang, Ricardo Henao:
Unsupervised Paraphrasing Consistency Training for Low Resource Named Entity Recognition. EMNLP (1) 2021: 5303-5308 - [c57]Vivek Subramanian, Matthew Engelhard, Samuel Berchuck, Liqun Chen, Ricardo Henao, Lawrence Carin:
SpanPredict: Extraction of Predictive Document Spans with Neural Attention. NAACL-HLT 2021: 5234-5258 - [c56]Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao:
Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer. NeurIPS 2021: 21229-21243 - [i42]Fanjie Kong, Xiao-Yang Liu, Ricardo Henao:
Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification. CoRR abs/2101.03154 (2021) - [i41]Meng Xia, Meenal K. Kheterpal, Samantha C. Wong, Christine Park, William Ratliff, Lawrence Carin, Ricardo Henao:
Malignancy Prediction and Lesion Identification from Clinical Dermatological Images. CoRR abs/2104.02652 (2021) - [i40]Fanjie Kong, Ricardo Henao:
Efficient Classification of Very Large Images with Tiny Objects. CoRR abs/2106.02694 (2021) - [i39]Qitong Gao, Dong Wang, Joshua D. Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic:
Imputation-Free Learning from Incomplete Observations. CoRR abs/2107.01983 (2021) - 2020
- [c55]Liqun Chen, Ke Bai, Chenyang Tao, Yizhe Zhang, Guoyin Wang, Wenlin Wang, Ricardo Henao, Lawrence Carin:
Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning. AAAI 2020: 7512-7520 - [c54]Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin:
Advancing weakly supervised cross-domain alignment with optimal transport. BMVC 2020 - [c53]Zidi Xiu, Chenyang Tao, Ricardo Henao:
Variational learning of individual survival distributions. CHIL 2020: 10-18 - [c52]Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao:
Survival cluster analysis. CHIL 2020: 60-68 - [c51]Rui Wang, Shijing Si, Guoyin Wang, Lei Zhang, Lawrence Carin, Ricardo Henao:
Integrating Task Specific Information into Pretrained Language Models for Low Resource Fine Tuning. EMNLP (Findings) 2020: 3181-3186 - [c50]Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin:
Learning Autoencoders with Relational Regularization. ICML 2020: 10576-10586 - [c49]Matthew Engelhard, Samuel Berchuck, Joshua D'Arcy, Ricardo Henao:
Neural Conditional Event Time Models. MLHC 2020: 223-244 - [i38]Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin:
Learning Autoencoders with Relational Regularization. CoRR abs/2002.02913 (2020) - [i37]Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin:
Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes. CoRR abs/2002.04752 (2020) - [i36]Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao:
Survival Cluster Analysis. CoRR abs/2003.00355 (2020) - [i35]Zidi Xiu, Chenyang Tao, Ricardo Henao:
Variational Learning of Individual Survival Distributions. CoRR abs/2003.04430 (2020) - [i34]Matthew Engelhard, Samuel Berchuck, Joshua D'Arcy, Ricardo Henao:
Neural Conditional Event Time Models. CoRR abs/2004.01376 (2020) - [i33]Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng, Michael J. Pencina, Lawrence Carin, Ricardo Henao:
Survival Analysis meets Counterfactual Inference. CoRR abs/2006.07756 (2020) - [i32]Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Ricardo Henao, Lawrence Carin:
Students Need More Attention: BERT-based AttentionModel for Small Data with Application to AutomaticPatient Message Triage. CoRR abs/2006.11991 (2020) - [i31]Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin:
Weakly supervised cross-domain alignment with optimal transport. CoRR abs/2008.06597 (2020) - [i30]Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao:
Variational Disentanglement for Rare Event Modeling. CoRR abs/2009.08541 (2020) - [i29]Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin:
Counterfactual Representation Learning with Balancing Weights. CoRR abs/2010.12618 (2020) - [i28]Junya Chen, Zidi Xiu, Benjamin Alan Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao:
Supercharging Imbalanced Data Learning With Causal Representation Transfer. CoRR abs/2011.12454 (2020) - [i27]Dong Wang, Yuewei Yang, Chenyang Tao, Fanjie Kong, Ricardo Henao, Lawrence Carin:
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models. CoRR abs/2012.03369 (2020) - [i26]Liqun Chen, Zhe Gan, Dong Wang, Jingjing Liu, Ricardo Henao, Lawrence Carin:
Wasserstein Contrastive Representation Distillation. CoRR abs/2012.08674 (2020)
2010 – 2019
- 2019
- [c48]Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin:
Communication-Efficient Stochastic Gradient MCMC for Neural Networks. AAAI 2019: 4173-4180 - [c47]Matias Benitez, James Tian, Mark Kelly, Vignesh Selvakumaran, Matthew Phelan, Maciej A. Mazurowski, Joseph Y. Lo, Geoffrey D. Rubin, Ricardo Henao:
Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports. Computer-Aided Diagnosis 2019: 109500V - [c46]Songyue Han, James Tian, Mark Kelly, Vignesh Selvakumaran, Ricardo Henao, Geoffrey D. Rubin, Joseph Y. Lo:
Classifying abnormalities in computed tomography radiology reports with rule-based and natural language processing models. Computer-Aided Diagnosis 2019: 109504H - [c45]David Dov, Shahar Z. Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin:
Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. MLHC 2019: 553-570 - [c44]Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin:
Improving Textual Network Learning with Variational Homophilic Embeddings. NeurIPS 2019: 2074-2085 - [c43]Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin:
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. NeurIPS 2019: 3387-3398 - [i25]David Dov, Shahar Ziv Kovalsky, Jonathan Cohen, Danielle Range, Ricardo Henao, Lawrence Carin:
Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. CoRR abs/1904.00839 (2019) - [i24]David Dov, Shahar Ziv Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin:
A Deep-Learning Algorithm for Thyroid Malignancy Prediction From Whole Slide Cytopathology Images. CoRR abs/1904.12739 (2019) - [i23]Paidamoyo Chapfuwa, Chenyang Tao, Lawrence Carin, Ricardo Henao:
Survival Function Matching for Calibrated Time-to-Event Predictions. CoRR abs/1905.08838 (2019) - [i22]Rui Wang, Guoyin Wang, Ricardo Henao:
Discriminative Clustering for Robust Unsupervised Domain Adaptation. CoRR abs/1905.13331 (2019) - [i21]Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin:
Improving Textual Network Learning with Variational Homophilic Embeddings. CoRR abs/1909.13456 (2019) - [i20]Pengyu Cheng, Chang Liu, Chunyuan Li, Dinghan Shen, Ricardo Henao, Lawrence Carin:
Straight-Through Estimator as Projected Wasserstein Gradient Flow. CoRR abs/1910.02176 (2019) - [i19]Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin:
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. CoRR abs/1910.04233 (2019) - 2018
- [c42]Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin:
Deconvolutional Latent-Variable Model for Text Sequence Matching. AAAI 2018: 5438-5445 - [c41]Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin:
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. ACL (1) 2018: 440-450 - [c40]Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa, Wenlin Wang, Guoyin Wang, Ricardo Henao, Lawrence Carin:
NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. ACL (1) 2018: 2041-2050 - [c39]Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin:
Joint Embedding of Words and Labels for Text Classification. ACL (1) 2018: 2321-2331 - [c38]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:
The Duke Health Data Science Internship Program: Integrating the Educational Mission into Real-World Research. AMIA 2018 - [c37]Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin:
Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. EMNLP 2018: 1829-1838 - [c36]Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao:
Adversarial Time-to-Event Modeling. ICML 2018: 734-743 - [c35]Liqun Chen, Chenyang Tao, Ruiyi Zhang, Ricardo Henao, Lawrence Carin:
Variational Inference and Model Selection with Generalized Evidence Bounds. ICML 2018: 892-901 - [c34]Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin:
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. ICML 2018: 4148-4157 - [c33]Chenyang Tao, Liqun Chen, Ricardo Henao, Jianfeng Feng, Lawrence Carin:
Chi-square Generative Adversarial Network. ICML 2018: 4894-4903 - [c32]Xinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin:
Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. MLHC 2018: 280-294 - [i18]Xinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin:
Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. CoRR abs/1801.05062 (2018) - [i17]Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao:
Adversarial Time-to-Event Modeling. CoRR abs/1804.03184 (2018) - [i16]Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin:
Joint Embedding of Words and Labels for Text Classification. CoRR abs/1805.04174 (2018) - [i15]Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa, Wenlin Wang, Guoyin Wang, Lawrence Carin, Ricardo Henao:
NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. CoRR abs/1805.05361 (2018) - [i14]Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin:
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. CoRR abs/1805.09843 (2018) - [i13]Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin:
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. CoRR abs/1806.02978 (2018) - [i12]Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin:
Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. CoRR abs/1808.09633 (2018) - 2017
- [j6]Ditte Høvenhoff Hald, Ricardo Henao, Ole Winther:
Gaussian process based independent analysis for temporal source separation in fMRI. NeuroImage 152: 563-574 (2017) - [c31]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:
Guiding Principles for the Duke Connected Care Predictive Modeling Pilot. AMIA 2017 - [c30]Shelley A. Rusincovitch, Ricardo Henao, Michael Gao, Lawrence Carin, Ursula Rogers, Nigel B. Neely, Mary Schilder, Daniel Costello, Eugenie Komives, Erich Huang:
Rationale and Design for the Duke Connected Care Predictive Modeling Pilot with a Medicare Shared Savings Program Population. AMIA 2017 - [c29]Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin:
Learning Generic Sentence Representations Using Convolutional Neural Networks. EMNLP 2017: 2390-2400 - [c28]Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin:
Stochastic Gradient Monomial Gamma Sampler. ICML 2017: 3996-4005 - [c27]Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin:
Adversarial Feature Matching for Text Generation. ICML 2017: 4006-4015 - [c26]Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin:
Deconvolutional Paragraph Representation Learning. NIPS 2017: 4169-4179 - [c25]Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin:
VAE Learning via Stein Variational Gradient Descent. NIPS 2017: 4236-4245 - [c24]Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin:
Adversarial Symmetric Variational Autoencoder. NIPS 2017: 4330-4339 - [c23]Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin:
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching. NIPS 2017: 5495-5503 - [i11]Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin:
Stein Variational Autoencoder. CoRR abs/1704.05155 (2017) - [i10]Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin:
Stochastic Gradient Monomial Gamma Sampler. CoRR abs/1706.01498 (2017) - [i9]Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin:
Adversarial Feature Matching for Text Generation. CoRR abs/1706.03850 (2017) - [i8]Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin:
Deconvolutional Paragraph Representation Learning. CoRR abs/1708.04729 (2017) - [i7]Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin:
Towards Understanding Adversarial Learning for Joint Distribution Matching. CoRR abs/1709.01215 (2017) - [i6]Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin:
Deconvolutional Latent-Variable Model for Text Sequence Matching. CoRR abs/1709.07109 (2017) - [i5]Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin:
Adversarial Symmetric Variational Autoencoder. CoRR abs/1711.04915 (2017) - 2016
- [j5]Ricardo Henao, James Lu, Joseph E. Lucas, Jeffrey M. Ferranti, Lawrence Carin:
Electronic Health Record Analysis via Deep Poisson Factor Models. J. Mach. Learn. Res. 17: 186:1-186:32 (2016) - [c22]Yizhe Zhang, Ricardo Henao, Lawrence Carin, Jianling Zhong, Alexander J. Hartemink:
Learning a Hybrid Architecture for Sequence Regression and Annotation. AAAI 2016: 1415-1421 - [c21]Zhao Song, Ricardo Henao, David E. Carlson, Lawrence Carin:
Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization. AISTATS 2016: 1347-1355 - [c20]Kai Fan, Yizhe Zhang, Ricardo Henao, Katherine A. Heller:
Triply Stochastic Variational Inference for Non-linear Beta Process Factor Analysis. ICDM 2016: 121-130 - [c19]Yizhe Zhang, Yue Zhao, Lawrence David, Ricardo Henao, Lawrence Carin:
Dynamic Poisson Factor Analysis. ICDM 2016: 1359-1364 - [c18]Yizhe Zhang, Ricardo Henao, Chunyuan Li, Lawrence Carin:
Bayesian Dictionary Learning with Gaussian Processes and Sigmoid Belief Networks. IJCAI 2016: 2364-2370 - [c17]Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin:
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling. NIPS 2016: 1741-1749 - [c16]Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin:
Variational Autoencoder for Deep Learning of Images, Labels and Captions. NIPS 2016: 2352-2360 - [c15]Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin:
Laplacian Hamiltonian Monte Carlo. ECML/PKDD (1) 2016: 98-114 - [p1]Zhe Gan, Xin Yuan, Ricardo Henao, Ephraim L. Tsalik, Lawrence Carin:
Inference of gene networks associated with the host response to infectious disease. Big Data over Networks 2016: 365-390 - [i4]Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin:
Variational Autoencoder for Deep Learning of Images, Labels and Captions. CoRR abs/1609.08976 (2016) - [i3]Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin:
Unsupervised Learning of Sentence Representations using Convolutional Neural Networks. CoRR abs/1611.07897 (2016) - 2015
- [c14]Zhe Gan, Ricardo Henao, David E. Carlson, Lawrence Carin:
Learning Deep Sigmoid Belief Networks with Data Augmentation. AISTATS 2015 - [c13]Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin:
Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood. ICML 2015: 1254-1263 - [c12]Zhe Gan, Changyou Chen, Ricardo Henao, David E. Carlson, Lawrence Carin:
Scalable Deep Poisson Factor Analysis for Topic Modeling. ICML 2015: 1823-1832 - [c11]Wenzhao Lian, Ricardo Henao, Vinayak A. Rao, Joseph E. Lucas, Lawrence Carin:
A Multitask Point Process Predictive Model. ICML 2015: 2030-2038 - [c10]Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson, Lawrence Carin:
Deep Temporal Sigmoid Belief Networks for Sequence Modeling. NIPS 2015: 2467-2475 - [c9]Ricardo Henao, Zhe Gan, James Lu, Lawrence Carin:
Deep Poisson Factor Modeling. NIPS 2015: 2800-2808 - [c8]Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin:
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings. NIPS 2015: 3222-3230 - [i2]Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson, Lawrence Carin:
Deep Temporal Sigmoid Belief Networks for Sequence Modeling. CoRR abs/1509.07087 (2015) - 2014
- [c7]Ricardo Henao, Xin Yuan, Lawrence Carin:
Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling. NIPS 2014: 1754-1762 - 2013
- [j4]Ashlee M. Benjamin, J. Will Thompson, Erik J. Soderblom, Scott J. Geromanos, Ricardo Henao, Virginia B. Kraus, M. Arthur Moseley, Joseph E. Lucas:
A flexible statistical model for alignment of label-free proteomics data - incorporating ion mobility and product ion information. BMC Bioinform. 14: 364 (2013) - [c6]Ricardo Henao, Jared Murray, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas:
Patient Clustering with Uncoded Text in Electronic Medical Records. AMIA 2013 - 2012
- [j3]Ricardo Henao, Ole Winther:
Predictive active set selection methods for Gaussian processes. Neurocomputing 80: 10-18 (2012) - [j2]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:
High Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections. IEEE Signal Process. Mag. 29(1): 108-123 (2012) - [c5]Ricardo Henao, J. Will Thompson, M. Arthur Moseley, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas:
Hierarchical factor modeling of proteomics data. ICCABS 2012: 1-6 - 2011
- [j1]Ricardo Henao, Ole Winther:
Sparse Linear Identifiable Multivariate Modeling. J. Mach. Learn. Res. 12: 863-905 (2011) - 2010
- [i1]Christian Walder, Ricardo Henao, Morten Mørup, Lars Kai Hansen:
Semi-Supervised Kernel PCA. CoRR abs/1008.1398 (2010)
2000 – 2009
- 2009
- [c4]Ricardo Henao, Ole Winther:
Bayesian Sparse Factor Models and DAGs Inference and Comparison. NIPS 2009: 736-744 - 2006
- [c3]Mauricio A. Álvarez, Ricardo Henao, Germán Castellanos-Domínguez, Juan Ignacio Godino-Llorente, Álvaro Ángel Orozco:
Kernel Principal Component Analysis through Time for Voice Disorder Classification. EMBC 2006: 5511-5514 - [c2]Mauricio A. Álvarez, Ricardo Henao:
Probabilistic Kernel Principal Component Analysis Through Time. ICONIP (1) 2006: 747-754 - 2004
- [c1]Carlos Lino Rengifo, Diego Andrés Alvarez, Ricardo Henao, Germán Castellanos, Jorge Eduardo Hurtado:
Active learning on the classification of voice pathologies. Odyssey 2004: 271-274
Coauthor Index
[c88] [i58] [j17] [i56] [j14] [j13] [c72] [i52] [c67] [c65] [c64] [i46] [i45] [i43] [j9] [j8] [c62] [c61] [c60] [c59] [c57] [c56] [i41] [i39] [c55] [c54] [c52] [c51] [c50] [i38] [i37] [i36] [i33] [i32] [i31] [i29] [i28] [i27] [i26] [c48] [c45] [c44] [c43] [i25] [i24] [i23] [i21] [i20] [i19] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [j5] [c22] [c21] [c19] [c18] [c17] [c16] [c15] [p1] [i4] [i3] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [i2] [c7] [c6] [j2] [c5]
Benjamin Goldstein 0001
aka: Benjamin Alan Goldstein
aka: Benjamin Alan Goldstein
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