Ricardo Henao

According to our database, Ricardo Henao authored at least 128 papers between 2004 and 2024.

Collaborative distances:

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

2024

Text Feature Adversarial Learning for Text Generation With Knowledge Transfer From GPT2.

Hao Zhang, Yulai Cong, Zhengjue Wang, Lei Zhang, Miaoyun Zhao, Liqun Chen, Shijing Si, Ricardo Henao, Lawrence Carin

IEEE Trans. Neural Networks Learn. Syst., May, 2024

Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare.

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

J. Am. Medical Informatics Assoc., February, 2024

Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance.

Chuan Hong, Molei Liu, Daniel Wojdyla, Jimmy Hickey, Michael J. Pencina, Ricardo Henao

J. Biomed. Informatics, January, 2024

A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis.

Wei A. Huang, Matthew Engelhard, Marika Coffman, Elliot D. Hill, Qin Weng, Abby Scheer, Gary Maslow, Ricardo Henao, Geraldine Dawson, Benjamin Alan Goldstein

J. Biomed. Informatics, 2024

Conditioning on Time is All You Need for Synthetic Survival Data Generation.

Mohd Ashhad, Ricardo Henao

CoRR, 2024

Transformer In-Context Learning for Categorical Data.

Aaron T. Wang, Ricardo Henao, Lawrence Carin

CoRR, 2024

Deep learning-driven pulmonary arteries and veins segmentation reveals demography-associated pulmonary vasculature anatomy.

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

CoRR, 2024

Personalized Federated Learning for Text Classification with Gradient-Free Prompt Tuning.

Rui Wang, Tong Yu, Ruiyi Zhang, Sungchul Kim, Ryan A. Rossi, Handong Zhao, Junda Wu, Subrata Mitra, Lina Yao, Ricardo Henao

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources.

Meng Xia, Jonathan Wilson, Benjamin Goldstein, Ricardo Henao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adaptive Discretization for Event PredicTion (ADEPT).

Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew Engelhard

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Learning Hierarchical Document Graphs From Multilevel Sentence Relations.

Hao Zhang, Chaojie Wang, Zhengjue Wang, Zhibin Duan, Bo Chen, Mingyuan Zhou, Ricardo Henao, Lawrence Carin

IEEE Trans. Neural Networks Learn. Syst., August, 2023

Enhancing early autism prediction based on electronic records using clinical narratives.

Junya Chen, Matthew Engelhard, Ricardo Henao, Samuel Berchuck, Brian Eichner, Eliana M. Perrin, Guillermo Sapiro, Geraldine Dawson

J. Biomed. Informatics, August, 2023

Calibration and Uncertainty in Neural Time-to-Event Modeling.

Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Irfan Khan, Karen Chandross, Michael J. Pencina, Lawrence Carin, Ricardo Henao

IEEE Trans. Neural Networks Learn. Syst., April, 2023

Reliable Active Learning via Influence Functions.

Meng Xia, Ricardo Henao

Trans. Mach. Learn. Res., 2023

Improving Event Time Prediction by Learning to Partition the Event Time Space.

Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew M. Engelhard

CoRR, 2023

Pushing the Efficiency Limit Using Structured Sparse Convolutions.

Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin

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

InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding.

Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mitigating Test-Time Bias for Fair Image Retrieval.

Fanjie Kong, Shuai Yuan, Weituo Hao, Ricardo Henao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hawkes Process with Flexible Triggering Kernels.

Yamac Alican Isik, Paidamoyo Chapfuwa, Connor Davis, Ricardo Henao

Proceedings of the Machine Learning for Healthcare Conference, 2023

Neural Insights for Digital Marketing Content Design.

Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti

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

An Effective Meaningful Way to Evaluate Survival Models.

Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner

Proceedings of the International Conference on Machine Learning, 2023

Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling.

Rui Wang, Pengyu Cheng, Ricardo Henao

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Estimating Total Correlation with Mutual Information Estimators.

Ke Bai, Pengyu Cheng, Weituo Hao, Ricardo Henao, Larry Carin

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Federated Domain Adaptation for Named Entity Recognition via Distilling with Heterogeneous Tag Sets.

Rui Wang, Tong Yu, Junda Wu, Handong Zhao, Sungchul Kim, Ruiyi Zhang, Subrata Mitra, Ricardo Henao

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

Few-Shot Composition Learning for Image Retrieval with Prompt Tuning.

Junda Wu, Rui Wang, Handong Zhao, Ruiyi Zhang, Chaochao Lu, Shuai Li, Ricardo Henao

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile.

Tianqi Yang, Ricardo Henao

PLoS Comput. Biol., September, 2022

Predicting in-hospital length of stay: a two-stage modeling approach to account for highly skewed data.

Zhenhui Xu, Congwen Zhao, Charles D. Scales, Ricardo Henao, Benjamin Alan Goldstein

BMC Medical Informatics Decis. Mak., 2022

Wasserstein Uncertainty Estimation for Adversarial Domain Matching.

Rui Wang, Ruiyi Zhang, Ricardo Henao

Frontiers Big Data, 2022

Toward Sustainable Continual Learning: Detection and Knowledge Repurposing of Similar Tasks.

Sijia Wang, Yoojin Choi, Junya Chen, Mostafa El-Khamy, Ricardo Henao

CoRR, 2022

Collaborative Anomaly Detection.

Ke Bai, Aonan Zhang, Zhizhong Li, Ricardo Henao, Chong Wang, Lawrence Carin

CoRR, 2022

Flexible Triggering Kernels for Hawkes Process Modeling.

Yamac Alican Isik, Connor Davis, Paidamoyo Chapfuwa, Ricardo Henao

CoRR, 2022

Capturing actionable dynamics with structured latent ordinary differential equations.

Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Gradient Importance Learning for Incomplete Observations.

Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic

Proceedings of the Tenth International Conference on Learning Representations, 2022

Wasserstein Cross-Lingual Alignment For Named Entity Recognition.

Rui Wang, Ricardo Henao

Proceedings of the IEEE International Conference on Acoustics, 2022

Context-aware Information-theoretic Causal De-biasing for Interactive Sequence Labeling.

Junda Wu, Rui Wang, Tong Yu, Ruiyi Zhang, Handong Zhao, Shuai Li, Ricardo Henao, Ani Nenkova

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Open World Classification with Adaptive Negative Samples.

Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Efficient Classification of Very Large Images with Tiny Objects.

Fanjie Kong, Ricardo Henao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data.

Matthew Engelhard, Ricardo Henao

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Few-Shot Class-Incremental Learning for Named Entity Recognition.

Rui Wang, Tong Yu, Handong Zhao, Sungchul Kim, Subrata Mitra, Ruiyi Zhang, Ricardo Henao

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Adaptive Multi-Channel Event Segmentation and Feature Extraction for Monitoring Health Outcomes.

Xichen She, Yaya Zhai, Ricardo Henao, Christopher W. Woods, Christopher Chiu, Geoffrey S. Ginsburg, Peter X. K. Song, Alfred O. Hero III

IEEE Trans. Biomed. Eng., 2021

Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes.

Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin

Medical Image Anal., 2021

Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images.

David Dov, Shahar Z. Kovalsky, Serge Assaad, Jonathan Cohen, Danielle Elliott Range, Avani A. Pendse, Ricardo Henao, Lawrence Carin

Medical Image Anal., 2021

Imputation-Free Learning from Incomplete Observations.

Qitong Gao, Dong Wang, Joshua D. Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic

CoRR, 2021

Malignancy Prediction and Lesion Identification from Clinical Dermatological Images.

Meng Xia, Meenal K. Kheterpal, Samantha C. Wong, Christine Park, William Ratliff, Lawrence Carin, Ricardo Henao

CoRR, 2021

Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification.

Fanjie Kong, Xiao-Yang Liu, Ricardo Henao

CoRR, 2021

Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer.

Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao

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

SpanPredict: Extraction of Predictive Document Spans with Neural Attention.

Vivek Subramanian, Matthew Engelhard, Samuel Berchuck, Liqun Chen, Ricardo Henao, Lawrence Carin

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Unsupervised Paraphrasing Consistency Training for Low Resource Named Entity Recognition.

Rui Wang, Ricardo Henao

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Wasserstein Contrastive Representation Distillation.

Liqun Chen, Dong Wang, Zhe Gan, Jingjing Liu, Ricardo Henao, Lawrence Carin

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

Affinitention nets: kernel perspective on attention architectures for set classification with applications to medical text and images.

David Dov, Serge Assaad, Shijing Si, Rui Wang, Hongteng Xu, Shahar Ziv Kovalsky, Jonathan Bell, Danielle Elliott Range, Jonathan Cohen, Ricardo Henao, Lawrence Carin

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

Enabling counterfactual survival analysis with balanced representations.

Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng, Michael J. Pencina, Lawrence Carin, Ricardo Henao

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

Counterfactual Representation Learning with Balancing Weights.

Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Variational Disentanglement for Rare Event Modeling.

Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models.

Dong Wang, Yuewei Yang, Chenyang Tao, Fanjie Kong, Ricardo Henao, Lawrence Carin

CoRR, 2020

Supercharging Imbalanced Data Learning With Causal Representation Transfer.

Junya Chen, Zidi Xiu, Benjamin Alan Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao

CoRR, 2020

Weakly supervised cross-domain alignment with optimal transport.

Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin

CoRR, 2020

Students Need More Attention: BERT-based AttentionModel for Small Data with Application to AutomaticPatient Message Triage.

Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Ricardo Henao, Lawrence Carin

CoRR, 2020

Survival Analysis meets Counterfactual Inference.

Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng, Michael J. Pencina, Lawrence Carin, Ricardo Henao

CoRR, 2020

Neural Conditional Event Time Models.

Matthew Engelhard, Samuel Berchuck, Joshua D'Arcy, Ricardo Henao

Proceedings of the Machine Learning for Healthcare Conference, 2020

Learning Autoencoders with Relational Regularization.

Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin

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

Integrating Task Specific Information into Pretrained Language Models for Low Resource Fine Tuning.

Rui Wang, Shijing Si, Guoyin Wang, Lei Zhang, Lawrence Carin, Ricardo Henao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Variational learning of individual survival distributions.

Zidi Xiu, Chenyang Tao, Ricardo Henao

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Survival cluster analysis.

Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Advancing weakly supervised cross-domain alignment with optimal transport.

Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin

Proceedings of the 31st British Machine Vision Conference 2020, 2020

Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning.

Liqun Chen, Ke Bai, Chenyang Tao, Yizhe Zhang, Guoyin Wang, Wenlin Wang, Ricardo Henao, Lawrence Carin

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Straight-Through Estimator as Projected Wasserstein Gradient Flow.

Pengyu Cheng, Chang Liu, Chunyuan Li, Dinghan Shen, Ricardo Henao, Lawrence Carin

CoRR, 2019

Discriminative Clustering for Robust Unsupervised Domain Adaptation.

Rui Wang, Guoyin Wang, Ricardo Henao

CoRR, 2019

Survival Function Matching for Calibrated Time-to-Event Predictions.

Paidamoyo Chapfuwa, Chenyang Tao, Lawrence Carin, Ricardo Henao

CoRR, 2019

A Deep-Learning Algorithm for Thyroid Malignancy Prediction From Whole Slide Cytopathology Images.

David Dov, Shahar Ziv Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin

CoRR, 2019

Improving Textual Network Learning with Variational Homophilic Embeddings.

Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin

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

Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods.

Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin

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

Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images.

David Dov, Shahar Z. Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin

Proceedings of the Machine Learning for Healthcare Conference, 2019

Classifying abnormalities in computed tomography radiology reports with rule-based and natural language processing models.

Songyue Han, James Tian, Mark Kelly, Vignesh Selvakumaran, Ricardo Henao, Geoffrey D. Rubin, Joseph Y. Lo

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports.

Matias Benitez, James Tian, Mark Kelly, Vignesh Selvakumaran, Matthew Phelan, Maciej A. Mazurowski, Joseph Y. Lo, Geoffrey D. Rubin, Ricardo Henao

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

Communication-Efficient Stochastic Gradient MCMC for Neural Networks.

Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Multi-Label Learning from Medical Plain Text with Convolutional Residual Models.

Xinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin

Proceedings of the Machine Learning for Healthcare Conference, 2018

Chi-square Generative Adversarial Network.

Chenyang Tao, Liqun Chen, Ricardo Henao, Jianfeng Feng, Lawrence Carin

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

JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets.

Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin

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

Variational Inference and Model Selection with Generalized Evidence Bounds.

Liqun Chen, Chenyang Tao, Ruiyi Zhang, Ricardo Henao, Lawrence Carin

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

Adversarial Time-to-Event Modeling.

Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao

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

Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment.

Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

The Duke Health Data Science Internship Program: Integrating the Educational Mission into Real-World Research.

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

Proceedings of the AMIA 2018, 2018

Joint Embedding of Words and Labels for Text Classification.

Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms.

Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing.

Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa, Wenlin Wang, Guoyin Wang, Ricardo Henao, Lawrence Carin

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Deconvolutional Latent-Variable Model for Text Sequence Matching.

Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin

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

2017

Gaussian process based independent analysis for temporal source separation in fMRI.

Ditte Høvenhoff Hald, Ricardo Henao, Ole Winther

NeuroImage, 2017

Towards Understanding Adversarial Learning for Joint Distribution Matching.

Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin

CoRR, 2017

Stein Variational Autoencoder.

Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin

CoRR, 2017

Deconvolutional Paragraph Representation Learning.

Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Adversarial Symmetric Variational Autoencoder.

Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

VAE Learning via Stein Variational Gradient Descent.

Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching.

Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Adversarial Feature Matching for Text Generation.

Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin

Proceedings of the 34th International Conference on Machine Learning, 2017

Stochastic Gradient Monomial Gamma Sampler.

Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin

Proceedings of the 34th International Conference on Machine Learning, 2017

Learning Generic Sentence Representations Using Convolutional Neural Networks.

Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Rationale and Design for the Duke Connected Care Predictive Modeling Pilot with a Medicare Shared Savings Program Population.

Shelley A. Rusincovitch, Ricardo Henao, Michael Gao, Lawrence Carin, Ursula Rogers, Nigel B. Neely, Mary Schilder, Daniel Costello, Eugenie Komives, Erich Huang

Proceedings of the AMIA 2017, 2017

Guiding Principles for the Duke Connected Care Predictive Modeling Pilot.

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

Proceedings of the AMIA 2017, 2017

2016

Electronic Health Record Analysis via Deep Poisson Factor Models.

Ricardo Henao, James Lu, Joseph E. Lucas, Jeffrey M. Ferranti, Lawrence Carin

J. Mach. Learn. Res., 2016

Unsupervised Learning of Sentence Representations using Convolutional Neural Networks.

Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin

CoRR, 2016

Laplacian Hamiltonian Monte Carlo.

Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Towards Unifying Hamiltonian Monte Carlo and Slice Sampling.

Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variational Autoencoder for Deep Learning of Images, Labels and Captions.

Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Bayesian Dictionary Learning with Gaussian Processes and Sigmoid Belief Networks.

Yizhe Zhang, Ricardo Henao, Chunyuan Li, Lawrence Carin

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Dynamic Poisson Factor Analysis.

Yizhe Zhang, Yue Zhao, Lawrence David, Ricardo Henao, Lawrence Carin

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Triply Stochastic Variational Inference for Non-linear Beta Process Factor Analysis.

Kai Fan, Yizhe Zhang, Ricardo Henao, Katherine A. Heller

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization.

Zhao Song, Ricardo Henao, David E. Carlson, Lawrence Carin

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Learning a Hybrid Architecture for Sequence Regression and Annotation.

Yizhe Zhang, Ricardo Henao, Lawrence Carin, Jianling Zhong, Alexander J. Hartemink

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Inference of gene networks associated with the host response to infectious disease.

Zhe Gan, Xin Yuan, Ricardo Henao, Ephraim L. Tsalik, Lawrence Carin

Proceedings of the Big Data over Networks, 2016

2015

Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings.

Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Deep Poisson Factor Modeling.

Ricardo Henao, Zhe Gan, James Lu, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Deep Temporal Sigmoid Belief Networks for Sequence Modeling.

Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood.

Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin

Proceedings of the 32nd International Conference on Machine Learning, 2015

A Multitask Point Process Predictive Model.

Wenzhao Lian, Ricardo Henao, Vinayak A. Rao, Joseph E. Lucas, Lawrence Carin

Proceedings of the 32nd International Conference on Machine Learning, 2015

Scalable Deep Poisson Factor Analysis for Topic Modeling.

Zhe Gan, Changyou Chen, Ricardo Henao, David E. Carlson, Lawrence Carin

Proceedings of the 32nd International Conference on Machine Learning, 2015

Learning Deep Sigmoid Belief Networks with Data Augmentation.

Zhe Gan, Ricardo Henao, David E. Carlson, Lawrence Carin

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling.

Ricardo Henao, Xin Yuan, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

A flexible statistical model for alignment of label-free proteomics data - incorporating ion mobility and product ion information.

Ashlee M. Benjamin, J. Will Thompson, Erik J. Soderblom, Scott J. Geromanos, Ricardo Henao, Virginia B. Kraus, M. Arthur Moseley, Joseph E. Lucas

BMC Bioinform., 2013

Patient Clustering with Uncoded Text in Electronic Medical Records.

Ricardo Henao, Jared Murray, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas

Proceedings of the AMIA 2013, 2013

2012

High Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections.

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

IEEE Signal Process. Mag., 2012

Predictive active set selection methods for Gaussian processes.

Ricardo Henao, Ole Winther

Neurocomputing, 2012

Hierarchical factor modeling of proteomics data.

Ricardo Henao, J. Will Thompson, M. Arthur Moseley, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas

Proceedings of the IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, 2012

2011

Sparse Linear Identifiable Multivariate Modeling.

Ricardo Henao, Ole Winther

J. Mach. Learn. Res., 2011

2010

Semi-Supervised Kernel PCA

Christian Walder, Ricardo Henao, Morten Mørup, Lars Kai Hansen

CoRR, 2010

2009

Bayesian Sparse Factor Models and DAGs Inference and Comparison.

Ricardo Henao, Ole Winther

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2006

Probabilistic Kernel Principal Component Analysis Through Time.

Mauricio A. Álvarez, Ricardo Henao

Proceedings of the Neural Information Processing, 13th International Conference, 2006

Kernel Principal Component Analysis through Time for Voice Disorder Classification.

Mauricio A. Álvarez, Ricardo Henao, Germán Castellanos-Domínguez, Juan Ignacio Godino-Llorente, Álvaro Ángel Orozco

Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

2004

Active learning on the classification of voice pathologies.

Carlos Lino Rengifo, Diego Andrés Alvarez, Ricardo Henao, Germán Castellanos, Jorge Eduardo Hurtado

Proceedings of the Odyssey 2004: The Speaker and Language Recognition Workshop, Toledo, Spain, May 31, 2004