Active learning on the classification of voice pathologies. - Carlos Lino Rengifo; Diego Andrés Alvarez; Ricardo Henao; Germán Castellanos; Jorge Eduardo Hurtado (Odyssey, 2004)

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 (EMBC, 2006)

Probabilistic Kernel Principal Component Analysis Through Time. - Mauricio A. Álvarez; Ricardo Henao (ICONIP (1), 2006)

Bayesian Sparse Factor Models and DAGs Inference and Comparison. - Ricardo Henao; Ole Winther (NIPS, 2009)

Semi-Supervised Kernel PCA - Christian Walder; Ricardo Henao; Morten Mørup; Lars Kai Hansen (CoRR, 2010)

Sparse Linear Identifiable Multivariate Modeling. - Ricardo Henao; Ole Winther (J. Mach. Learn. Res., 2011)

Hierarchical factor modeling of proteomics data. - Ricardo Henao; J. Will Thompson; M. Arthur Moseley; Geoffrey S. Ginsburg; Lawrence Carin; Joseph E. Lucas (ICCABS, 2012)

Predictive active set selection methods for Gaussian processes. - Ricardo Henao; Ole Winther (Neurocomputing, 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)

Patient Clustering with Uncoded Text in Electronic Medical Records. - Ricardo Henao; Jared Murray; Geoffrey S. Ginsburg; Lawrence Carin; Joseph E. Lucas (AMIA, 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)

Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling. - Ricardo Henao; Xin Yuan 002; Lawrence Carin (NIPS, 2014)

Learning Deep Sigmoid Belief Networks with Data Augmentation. - Zhe Gan; Ricardo Henao; David E. Carlson; Lawrence Carin (AISTATS, 2015)

Scalable Deep Poisson Factor Analysis for Topic Modeling. - Zhe Gan; Changyou Chen; Ricardo Henao; David E. Carlson; Lawrence Carin (ICML, 2015)

A Multitask Point Process Predictive Model. - Wenzhao Lian; Ricardo Henao; Vinayak A. Rao; Joseph E. Lucas; Lawrence Carin (ICML, 2015)

Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood. - Xin Yuan 002; Ricardo Henao; Ephraim Tsalik; Raymond Langley; Lawrence Carin (ICML, 2015)

Deep Temporal Sigmoid Belief Networks for Sequence Modeling. - Zhe Gan; Chunyuan Li; Ricardo Henao; David E. Carlson; Lawrence Carin (NIPS, 2015)

Deep Poisson Factor Modeling. - Ricardo Henao; Zhe Gan; James Lu; Lawrence Carin (NIPS, 2015)

Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings. - Piyush Rai; Changwei Hu; Ricardo Henao; Lawrence Carin (NIPS, 2015)

Inference of gene networks associated with the host response to infectious disease. - Zhe Gan; Xin Yuan 002; Ricardo Henao; Ephraim L. Tsalik; Lawrence Carin (Big Data over Networks, 2016)

Learning a Hybrid Architecture for Sequence Regression and Annotation. - Yizhe Zhang 002; Ricardo Henao; Lawrence Carin; Jianling Zhong; Alexander J. Hartemink (AAAI, 2016)

Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization. - Zhao Song 001; Ricardo Henao; David E. Carlson; Lawrence Carin (AISTATS, 2016)

Triply Stochastic Variational Inference for Non-linear Beta Process Factor Analysis. - Kai Fan 002; Yizhe Zhang 002; Ricardo Henao; Katherine A. Heller (ICDM, 2016)

Dynamic Poisson Factor Analysis. - Yizhe Zhang 002; Yue Zhao; Lawrence David; Ricardo Henao; Lawrence Carin (ICDM, 2016)

Bayesian Dictionary Learning with Gaussian Processes and Sigmoid Belief Networks. - Yizhe Zhang 002; Ricardo Henao; Chunyuan Li; Lawrence Carin (IJCAI, 2016)

Variational Autoencoder for Deep Learning of Images, Labels and Captions. - Yunchen Pu; Zhe Gan; Ricardo Henao; Xin Yuan 002; Chunyuan Li; Andrew Stevens 005; Lawrence Carin (NIPS, 2016)

Towards Unifying Hamiltonian Monte Carlo and Slice Sampling. - Yizhe Zhang 002; Xiangyu Wang 006; Changyou Chen; Ricardo Henao; Kai Fan 002; Lawrence Carin (NIPS, 2016)

Laplacian Hamiltonian Monte Carlo. - Yizhe Zhang 002; Changyou Chen; Ricardo Henao; Lawrence Carin (ECML/PKDD (1), 2016)

Unsupervised Learning of Sentence Representations using Convolutional Neural Networks. - Zhe Gan; Yunchen Pu; Ricardo Henao; Chunyuan Li; Xiaodong He 001; Lawrence Carin (CoRR, 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)

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; et al. (AMIA, 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 (AMIA, 2017)

Learning Generic Sentence Representations Using Convolutional Neural Networks. - Zhe Gan; Yunchen Pu; Ricardo Henao; Chunyuan Li; Xiaodong He 001; Lawrence Carin (EMNLP, 2017)

Stochastic Gradient Monomial Gamma Sampler. - Yizhe Zhang 002; Changyou Chen; Zhe Gan; Ricardo Henao; Lawrence Carin (ICML, 2017)

Adversarial Feature Matching for Text Generation. - Yizhe Zhang 002; Zhe Gan; Kai Fan 002; Zhi Chen 009; Ricardo Henao; Dinghan Shen; Lawrence Carin (ICML, 2017)

ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching. - Chunyuan Li; Hao Liu 015; Changyou Chen; Yunchen Pu; Liqun Chen 001; Ricardo Henao; Lawrence Carin (NIPS, 2017)

VAE Learning via Stein Variational Gradient Descent. - Yunchen Pu; Zhe Gan; Ricardo Henao; Chunyuan Li; Shaobo Han; Lawrence Carin (NIPS, 2017)

Adversarial Symmetric Variational Autoencoder. - Yunchen Pu; Weiyao Wang 002; Ricardo Henao; Liqun Chen 001; Zhe Gan; Chunyuan Li; Lawrence Carin (NIPS, 2017)

Deconvolutional Paragraph Representation Learning. - Yizhe Zhang 002; Dinghan Shen; Guoyin Wang 002; Zhe Gan; Ricardo Henao; Lawrence Carin (NIPS, 2017)

Stein Variational Autoencoder. - Yunchen Pu; Zhe Gan; Ricardo Henao; Chunyuan Li; Shaobo Han; Lawrence Carin (CoRR, 2017)

Towards Understanding Adversarial Learning for Joint Distribution Matching. - Chunyuan Li; Hao Liu 015; Changyou Chen; Yunchen Pu; Liqun Chen 001; Ricardo Henao; Lawrence Carin (CoRR, 2017)

Gaussian process based independent analysis for temporal source separation in fMRI. - Ditte Høvenhoff Hald; Ricardo Henao; Ole Winther (NeuroImage, 2017)

Deconvolutional Latent-Variable Model for Text Sequence Matching. - Dinghan Shen; Yizhe Zhang 002; Ricardo Henao; Qinliang Su; Lawrence Carin (AAAI, 2018)

NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. - Dinghan Shen; Qinliang Su; Paidamoyo Chapfuwa; Wenlin Wang; Guoyin Wang 002; Ricardo Henao; Lawrence Carin (ACL (1), 2018)

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. - Dinghan Shen; Guoyin Wang 002; Wenlin Wang; Martin Renqiang Min; Qinliang Su; Yizhe Zhang 002; Chunyuan Li; Ricardo Henao; Lawrence Carin (ACL (1), 2018)

Joint Embedding of Words and Labels for Text Classification. - Guoyin Wang 002; Chunyuan Li; Wenlin Wang; Yizhe Zhang 002; Dinghan Shen; Xinyuan Zhang 001; Ricardo Henao; Lawrence Carin (ACL (1), 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 (AMIA, 2018)

Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. - Dinghan Shen; Xinyuan Zhang 001; Ricardo Henao; Lawrence Carin (EMNLP, 2018)

Adversarial Time-to-Event Modeling. - Paidamoyo Chapfuwa; Chenyang Tao; Chunyuan Li; Courtney Page; Benjamin Alan Goldstein; Lawrence Carin; Ricardo Henao (ICML, 2018)

Variational Inference and Model Selection with Generalized Evidence Bounds. - Liqun Chen 001; Chenyang Tao; Ruiyi Zhang 002; Ricardo Henao; Lawrence Carin (ICML, 2018)

JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. - Yunchen Pu; Shuyang Dai; Zhe Gan; Weiyao Wang 002; Guoyin Wang 002; Yizhe Zhang 002; Ricardo Henao; Lawrence Carin (ICML, 2018)

Chi-square Generative Adversarial Network. - Chenyang Tao; Liqun Chen 001; Ricardo Henao; Jianfeng Feng; Lawrence Carin (ICML, 2018)

Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. - Xinyuan Zhang 001; Ricardo Henao; Zhe Gan; Yitong Li 001; Lawrence Carin (MLHC, 2018)

Communication-Efficient Stochastic Gradient MCMC for Neural Networks. - Chunyuan Li; Changyou Chen; Yunchen Pu; Ricardo Henao; Lawrence Carin (AAAI, 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 (Computer-Aided Diagnosis, 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 (Computer-Aided Diagnosis, 2019)

Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. - David Dov; Shahar Z. Kovalsky; Jonathan Cohen 004; Danielle Elliott Range; Ricardo Henao; Lawrence Carin (MLHC, 2019)

Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. - Kevin J. Liang; Guoyin Wang 002; Yitong Li 001; Ricardo Henao; Lawrence Carin (NeurIPS, 2019)

Improving Textual Network Learning with Variational Homophilic Embeddings. - Wenlin Wang; Chenyang Tao; Zhe Gan; Guoyin Wang 002; Liqun Chen 001; Xinyuan Zhang 001; Ruiyi Zhang 002; Qian Yang 003; Ricardo Henao; Lawrence Carin (NeurIPS, 2019)

A Deep-Learning Algorithm for Thyroid Malignancy Prediction From Whole Slide Cytopathology Images. - David Dov; Shahar Ziv Kovalsky; Jonathan Cohen 004; Danielle Elliott Range; Ricardo Henao; Lawrence Carin (CoRR, 2019)

Survival Function Matching for Calibrated Time-to-Event Predictions. - Paidamoyo Chapfuwa; Chenyang Tao; Lawrence Carin; Ricardo Henao (CoRR, 2019)

Discriminative Clustering for Robust Unsupervised Domain Adaptation. - Rui Wang 088; Guoyin Wang 002; Ricardo Henao (CoRR, 2019)

Straight-Through Estimator as Projected Wasserstein Gradient Flow. - Pengyu Cheng; Chang Liu 030; Chunyuan Li; Dinghan Shen; Ricardo Henao; Lawrence Carin (CoRR, 2019)

Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning. - Liqun Chen 001; Ke Bai 001; Chenyang Tao; Yizhe Zhang 002; Guoyin Wang 002; Wenlin Wang; Ricardo Henao; Lawrence Carin (AAAI, 2020)

Advancing weakly supervised cross-domain alignment with optimal transport. - Siyang Yuan; Ke Bai 001; Liqun Chen 001; Yizhe Zhang 002; Chenyang Tao; Chunyuan Li; Guoyin Wang 002; Ricardo Henao; Lawrence Carin (BMVC, 2020)

Survival cluster analysis. - Paidamoyo Chapfuwa; Chunyuan Li; Nikhil Mehta 002; Lawrence Carin; Ricardo Henao (CHIL, 2020)

Variational learning of individual survival distributions. - Zidi Xiu; Chenyang Tao; Ricardo Henao (CHIL, 2020)

Integrating Task Specific Information into Pretrained Language Models for Low Resource Fine Tuning. - Rui Wang 088; Shijing Si; Guoyin Wang 002; Lei Zhang; Lawrence Carin; Ricardo Henao (EMNLP (Findings), 2020)

Learning Autoencoders with Relational Regularization. - Hongteng Xu; Dixin Luo; Ricardo Henao; Svati Shah; Lawrence Carin (ICML, 2020)

Neural Conditional Event Time Models. - Matthew Engelhard; Samuel Berchuck; Joshua D'Arcy; Ricardo Henao (MLHC, 2020)

Survival Analysis meets Counterfactual Inference. - Paidamoyo Chapfuwa; Serge Assaad; Shuxi Zeng; Michael J. Pencina; Lawrence Carin; Ricardo Henao (CoRR, 2020)

Students Need More Attention: BERT-based AttentionModel for Small Data with Application to AutomaticPatient Message Triage. - Shijing Si; Rui Wang 088; Jedrek Wosik; Hao Zhang 050; David Dov; Guoyin Wang 002; Ricardo Henao; Lawrence Carin (CoRR, 2020)

Weakly supervised cross-domain alignment with optimal transport. - Siyang Yuan; Ke Bai 001; Liqun Chen 001; Yizhe Zhang 002; Chenyang Tao; Chunyuan Li; Guoyin Wang 002; 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)

Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models. - Dong Wang 037; Yuewei Yang; Chenyang Tao; Fanjie Kong; Ricardo Henao; Lawrence Carin (CoRR, 2020)

Variational Disentanglement for Rare Event Modeling. - Zidi Xiu; Chenyang Tao; Michael Gao; Connor Davis; Benjamin Alan Goldstein; Ricardo Henao (AAAI, 2021)

Counterfactual Representation Learning with Balancing Weights. - Serge Assaad; Shuxi Zeng; Chenyang Tao; Shounak Datta; Nikhil Mehta 002; Ricardo Henao; Fan Li; Lawrence Carin (AISTATS, 2021)

Enabling counterfactual survival analysis with balanced representations. - Paidamoyo Chapfuwa; Serge Assaad; Shuxi Zeng; Michael J. Pencina; Lawrence Carin; Ricardo Henao (CHIL, 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 088; Hongteng Xu; Shahar Ziv Kovalsky; Jonathan Bell; Danielle Elliott Range; Jonathan Cohen 004; Ricardo Henao; Lawrence Carin (CHIL, 2021)

Wasserstein Contrastive Representation Distillation. - Liqun Chen 001; Dong Wang 037; Zhe Gan; Jingjing Liu 001; Ricardo Henao; Lawrence Carin (CVPR, 2021)

Unsupervised Paraphrasing Consistency Training for Low Resource Named Entity Recognition. - Rui Wang 088; Ricardo Henao (EMNLP (1), 2021)

SpanPredict: Extraction of Predictive Document Spans with Neural Attention. - Vivek Subramanian; Matthew Engelhard; Samuel Berchuck; Liqun Chen 001; Ricardo Henao; Lawrence Carin (NAACL-HLT, 2021)

Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer. - Junya Chen; Zidi Xiu; Benjamin Goldstein 001; Ricardo Henao; Lawrence Carin; Chenyang Tao (NeurIPS, 2021)

Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification. - Fanjie Kong; Xiao-Yang Liu; Ricardo Henao (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)

Imputation-Free Learning from Incomplete Observations. - Qitong Gao; Dong Wang 037; Joshua D. Amason; Siyang Yuan; Chenyang Tao; Ricardo Henao; Majda Hadziahmetovic; Lawrence Carin; Miroslav Pajic (CoRR, 2021)

Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images. - David Dov; Shahar Z. Kovalsky; Serge Assaad; Jonathan Cohen 004; Danielle Elliott Range; Avani A. Pendse; Ricardo Henao; Lawrence Carin (Medical Image Anal., 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)

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)

Few-Shot Class-Incremental Learning for Named Entity Recognition. - Rui Wang 088; Tong Yu 001; Handong Zhao; Sungchul Kim; Subrata Mitra; Ruiyi Zhang 002; Ricardo Henao (ACL (1), 2022)

Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data. - Matthew Engelhard; Ricardo Henao (AISTATS, 2022)

Efficient Classification of Very Large Images with Tiny Objects. - Fanjie Kong; Ricardo Henao (CVPR, 2022)

Open World Classification with Adaptive Negative Samples. - Ke Bai 001; Guoyin Wang 002; Jiwei Li 001; Sunghyun Park; Sungjin Lee; Puyang Xu; Ricardo Henao; Lawrence Carin (EMNLP, 2022)

Context-aware Information-theoretic Causal De-biasing for Interactive Sequence Labeling. - Junda Wu; Rui Wang 088; Tong Yu 001; Ruiyi Zhang 002; Handong Zhao; Shuai Li 010; Ricardo Henao; Ani Nenkova (EMNLP (Findings), 2022)

Wasserstein Cross-Lingual Alignment For Named Entity Recognition. - Rui Wang 088; Ricardo Henao (ICASSP, 2022)

Gradient Importance Learning for Incomplete Observations. - Qitong Gao; Dong Wang 037; Joshua David Amason; Siyang Yuan; Chenyang Tao; Ricardo Henao; Majda Hadziahmetovic; Lawrence Carin; Miroslav Pajic (ICLR, 2022)

Capturing actionable dynamics with structured latent ordinary differential equations. - Paidamoyo Chapfuwa; Sherri Rose; Lawrence Carin; Edward Meeds; Ricardo Henao (UAI, 2022)

Flexible Triggering Kernels for Hawkes Process Modeling. - Yamac Alican Isik; Connor Davis; Paidamoyo Chapfuwa; Ricardo Henao (CoRR, 2022)

Collaborative Anomaly Detection. - Ke Bai 001; Aonan Zhang; Zhizhong Li 002; Ricardo Henao; Chong Wang 002; Lawrence Carin (CoRR, 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)

Wasserstein Uncertainty Estimation for Adversarial Domain Matching. - Rui Wang 088; Ruiyi Zhang 002; Ricardo Henao (Frontiers Big Data, 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)

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., 2022)

Few-Shot Composition Learning for Image Retrieval with Prompt Tuning. - Junda Wu; Rui Wang 088; Handong Zhao; Ruiyi Zhang 002; Chaochao Lu; Shuai Li 010; Ricardo Henao (AAAI, 2023)

Federated Domain Adaptation for Named Entity Recognition via Distilling with Heterogeneous Tag Sets. - Rui Wang 088; Tong Yu 001; Junda Wu; Handong Zhao; Sungchul Kim; Ruiyi Zhang 002; Subrata Mitra; Ricardo Henao (ACL (Findings), 2023)

Estimating Total Correlation with Mutual Information Estimators. - Ke Bai 001; Pengyu Cheng; Weituo Hao; Ricardo Henao; Larry Carin (AISTATS, 2023)

Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling. - Rui Wang 088; Pengyu Cheng; Ricardo Henao (AISTATS, 2023)

An Effective Meaningful Way to Evaluate Survival Models. - Shiang Qi; Neeraj Kumar 002; Mahtab Farrokh; Weijie Sun 004; Li-Hao Kuan; Rajesh Ranganath; Ricardo Henao; Russell Greiner (ICML, 2023)

Neural Insights for Digital Marketing Content Design. - Fanjie Kong; Yuan Li 031; Houssam Nassif; Tanner Fiez; Ricardo Henao; Shreya Chakrabarti (KDD, 2023)

Hawkes Process with Flexible Triggering Kernels. - Yamac Alican Isik; Paidamoyo Chapfuwa; Connor Davis; Ricardo Henao (MLHC, 2023)

Mitigating Test-Time Bias for Fair Image Retrieval. - Fanjie Kong; Shuai Yuan; Weituo Hao; Ricardo Henao (NeurIPS, 2023)

InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. - Junda Wu; Tong Yu 001; Rui Wang 088; Zhao Song 002; Ruiyi Zhang 002; Handong Zhao; Chaochao Lu; Shuai Li 010; Ricardo Henao (NeurIPS, 2023)

Pushing the Efficiency Limit Using Structured Sparse Convolutions. - Vinay Kumar Verma; Nikhil Mehta 002; Shijing Si; Ricardo Henao; Lawrence Carin (WACV, 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)

Reliable Active Learning via Influence Functions. - Meng Xia; Ricardo Henao (Trans. Mach. Learn. Res., 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., 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, 2023)

Learning Hierarchical Document Graphs From Multilevel Sentence Relations. - Hao Zhang 050; Chaojie Wang 001; Zhengjue Wang; Zhibin Duan; Bo Chen 001; Mingyuan Zhou; Ricardo Henao; Lawrence Carin (IEEE Trans. Neural Networks Learn. Syst., 2023)

Adaptive Discretization for Event PredicTion (ADEPT). - Jimmy Hickey; Ricardo Henao; Daniel Wojdyla; Michael J. Pencina; Matthew Engelhard (AISTATS, 2024)

Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources. - Meng Xia; Jonathan Wilson; Benjamin Goldstein 001; Ricardo Henao (ICML, 2024)

Personalized Federated Learning for Text Classification with Gradient-Free Prompt Tuning. - Rui Wang 088; Tong Yu 001; Ruiyi Zhang 002; Sungchul Kim; Ryan A. Rossi; Handong Zhao; Junda Wu; Subrata Mitra; Lina Yao 001; Ricardo Henao (NAACL-HLT (Findings), 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; et al. (CoRR, 2024)

Transformer In-Context Learning for Categorical Data. - Aaron T. Wang; Ricardo Henao; Lawrence Carin (CoRR, 2024)

Conditioning on Time is All You Need for Synthetic Survival Data Generation. - Mohd Ashhad; Ricardo Henao (CoRR, 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)

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, 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 001; John Eric Jelovsek; Cara O'Brien; Nancy Walden; Matthew Elmore; Amanda B. Parrish; Scott Elengold; Kay S. Lytle; et al. (J. Am. Medical Informatics Assoc., 2024)

Text Feature Adversarial Learning for Text Generation With Knowledge Transfer From GPT2. - Hao Zhang 050; Yulai Cong; Zhengjue Wang; Lei Zhang; Miaoyun Zhao; Liqun Chen 001; Shijing Si; Ricardo Henao; Lawrence Carin (IEEE Trans. Neural Networks Learn. Syst., 2024)

Cross-Modal Imputation and Uncertainty Estimation for Spatial Transcriptomics. - Xiangyu Guo; Ricardo Henao (AISTATS, 2025)

Learning to Substitute Words with Model-based Score Ranking. - Hongye Liu; Ricardo Henao (NAACL (Long Papers), 2025)

Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models. - Matthew Engelhard; Daniel Wojdyla; Haoyuan Wang; Michael J. Pencina; Ricardo Henao (Artif. Intell. Medicine, 2025)

Learning Survival Distributions with the Asymmetric Laplace Distribution. - Deming Sheng; Ricardo Henao (CoRR, 2025)

Model Recycling Framework for Multi-Source Data-Free Supervised Transfer Learning. - Sijia Wang; Ricardo Henao (CoRR, 2025)