Artificial neural network approach to data analysis and parameter estimation in experimental spectroscopy. - Mehmed M. Kantardzic; Anna Goldenberg; Troy E. Howe; Peter Faguy (Informatica (Slovenia), 2001)

Tractable learning of large Bayes net structures from sparse data. - Anna Goldenberg; Andrew W. Moore 001 (ICML, 2004)

Bayes net graphs to understand co-authorship networks? - Anna Goldenberg; Andrew W. Moore 001 (LinkKDD, 2005)

Exploratory Study of a New Model for Evolving Networks. - Anna Goldenberg; Alice X. Zheng (SNA@ICML, 2006)

A Survey of Statistical Network Models. - Anna Goldenberg; Alice X. Zheng; Stephen E. Fienberg; Edoardo M. Airoldi (Found. Trends Mach. Learn., 2009)

Unsupervised detection of genes of influence in lung cancer using biological networks. - Anna Goldenberg; Sara Mostafavi; Gerald T. Quon; Paul C. Boutros; Quaid Morris (Bioinform., 2011)

Mixture Model for Sub-Phenotyping in GWAS. - David Warde-Farley; Michael Brudno; Quaid Morris; Anna Goldenberg (Pacific Symposium on Biocomputing, 2012)

Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study. - Mohammed Alshalalfa; Gary D. Bader; Anna Goldenberg; Quaid Morris; Reda Alhajj (BMC Syst. Biol., 2012)

A probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information. - Yue Li 017; Anna Goldenberg; Ka-Chun Wong; Zhaolei Zhang (Bioinform., 2014)

EquiNMF: Graph Regularized Multiview Nonnegative Matrix Factorization. - Daniel Hidru; Anna Goldenberg (CoRR, 2014)

Gradient-based Laplacian Feature Selection. - Bo Wang 044; Anna Goldenberg (CoRR, 2014)

Combining exome and gene expression datasets in one graphical model of disease to empower the discovery of disease mechanisms. - Aziz M. Mezlini; Fabio Fuligni; Adam Shlien; Anna Goldenberg (CoRR, 2015)

Subtyping: What It is and Its Role in Precision Medicine. - Suchi Saria; Anna Goldenberg (IEEE Intell. Syst., 2015)

JBASE: Joint Bayesian Analysis of Subphenotypes and Epistasis. - Recep Colak; TaeHyung Kim; Hilal Kazan; Yoomi Oh; Miguel Cruz; Adan Valladares-Salgado; Jesus Peralta; Jorge Escobedo; Esteban J. Parra; Philip M. Kim; Anna Goldenberg (Bioinform., 2016)

PharmacoGx: an R package for analysis of large pharmacogenomic datasets. - Petr Smirnov; Zhaleh Safikhani; Nehme Hachem; Dong Wang; Adrian She; Catharina Olsen; Mark Freeman 002; Heather Marie Selby; Deena M. A. Gendoo; Patrick Grossmann; Andrew H. Beck; Hugo J. W. L. Aerts; et al. (Bioinform., 2016)

Modeling trajectories of mental health: challenges and opportunities. - Lauren Erdman; Ekansh Sharma; Eva Unternaehrer; Shantala A. Hari Dass; Kieran J. O'Donnell; Sara Mostafavi; Rachel Edgar; Michael S. Kobor; Hélène Gaudreau; Michael J. Meaney 001; Anna Goldenberg (CoRR, 2016)

Safikhani et al. reply. - Zhaleh Safikhani; Nehme Hachem; Petr Smirnov; Mark Freeman 002; Anna Goldenberg; Nicolai J. Birkbak; Andrew H. Beck; Hugo J. W. L. Aerts; John Quackenbush; Benjamin Haibe-Kains (Nat., 2016)

Dropout Feature Ranking for Deep Learning Models. - Chun-Hao Chang; Ladislav Rampásek; Anna Goldenberg (CoRR, 2017)

Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases. - Aziz M. Mezlini; Anna Goldenberg (PLoS Comput. Biol., 2017)

Vicus: Exploiting local structures to improve network-based analysis of biological data. - Bo Wang 044; Lin Huang; Yuke Zhu; Anshul Kundaje; Serafim Batzoglou; Anna Goldenberg (PLoS Comput. Biol., 2017)

Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU. - Sana Tonekaboni; Mjaye Mazwi; Peter Laussen; Danny Eytan; Robert Greer; Sebastian D. Goodfellow; Andrew J. Goodwin; Michael Brudno; Anna Goldenberg (MLHC, 2018)

Explaining Image Classifiers by Adaptive Dropout and Generative In-filling. - Chun-Hao Chang; Elliot Creager; Anna Goldenberg; David Duvenaud (CoRR, 2018)

Stochastic Combinatorial Ensembles for Defending Against Adversarial Examples. - George-Alexandru Adam; Petr Smirnov; Anna Goldenberg; David Duvenaud; Benjamin Haibe-Kains (CoRR, 2018)

Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. - Bret Nestor; Matthew B. A. McDermott; Geeticka Chauhan; Tristan Naumann; Michael C. Hughes; Anna Goldenberg; Marzyeh Ghassemi (CoRR, 2018)

Dynamic Measurement Scheduling for Adverse Event Forecasting using Deep RL. - Chun-Hao Chang; Mingjie Mai; Anna Goldenberg (CoRR, 2018)

Explaining Image Classifiers by Counterfactual Generation. - Chun-Hao Chang; Elliot Creager; Anna Goldenberg; David Duvenaud (ICLR (Poster), 2019)

Dynamic Measurement Scheduling for Event Forecasting using Deep RL. - Chun-Hao Chang; Mingjie Mai; Anna Goldenberg (ICML, 2019)

Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. - Bret Nestor; Matthew B. A. McDermott; Willie Boag; Gabriela Berner; Tristan Naumann; Michael C. Hughes; Anna Goldenberg; Marzyeh Ghassemi (MLHC, 2019)

What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. - Sana Tonekaboni; Shalmali Joshi; Melissa D. McCradden; Anna Goldenberg (MLHC, 2019)

Dr.VAE: improving drug response prediction via modeling of drug perturbation effects. - Ladislav Rampásek; Daniel Hidru; Petr Smirnov; Benjamin Haibe-Kains; Anna Goldenberg (Bioinform., 2019)

The False Positive Control Lasso. - Erik Drysdale; Yingwei Peng; Timothy P. Hanna; Paul Nguyen; Anna Goldenberg (CoRR, 2019)

Reducing Adversarial Example Transferability Using Gradient Regularization. - George Adam; Petr Smirnov; Benjamin Haibe-Kains; Anna Goldenberg (CoRR, 2019)

Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities. - Marinka Zitnik; Francis Nguyen; Bo Wang 044; Jure Leskovec; Anna Goldenberg; Michael M. Hoffman (Inf. Fusion, 2019)

Predicting Obstructive Hydronephrosis Based on Ultrasound Alone. - Lauren Erdman; Marta Skreta; Mandy Rickard; Carson McLean; Aziz Mezlini; Daniel T. Keefe; Anne-Sophie Blais; Michael Brudno; Armando J. Lorenzo; Anna Goldenberg (MICCAI (3), 2020)

Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation. - George-Alexandru Adam; Chun-Hao Kingsley Chang; Benjamin Haibe-Kains; Anna Goldenberg (MLHC, 2020)

Preparing a Clinical Support Model for Silent Mode in General Internal Medicine. - Bret Nestor; Liam G. McCoy; Amol Verma; Chloé Pou-Prom; Joshua Murray; Sebnem Kuzulugil; David Dai; Muhammad Mamdani; Anna Goldenberg; Marzyeh Ghassemi (MLHC, 2020)

What went wrong and when? Instance-wise feature importance for time-series black-box models. - Sana Tonekaboni; Shalmali Joshi; Kieran Campbell; David Duvenaud; Anna Goldenberg (NeurIPS, 2020)

What went wrong and when? Instance-wise Feature Importance for Time-series Models. - Sana Tonekaboni; Shalmali Joshi; David Duvenaud; Anna Goldenberg (CoRR, 2020)

Using Generative Models for Pediatric wbMRI. - Alex Chang; Vinith M. Suriyakumar; Abhishek Moturu; Nipaporn Tewattanarat; Andrea Doria 001; Anna Goldenberg (CoRR, 2020)

A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. - Matthew B. A. McDermott; Bret Nestor; Evan Kim; Wancong Zhang; Anna Goldenberg; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2020)

Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds. - Erik Drysdale; Devin Singh; Anna Goldenberg (CoRR, 2020)

Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. - Melissa D. McCradden; Shalmali Joshi; James A. Anderson; Mjaye Mazwi; Anna Goldenberg; Randi Zlotnik Shaul (J. Am. Medical Informatics Assoc., 2020)

A comprehensive EHR timeseries pre-training benchmark. - Matthew B. A. McDermott; Bret Nestor; Evan Kim; Wancong Zhang; Anna Goldenberg; Peter Szolovits; Marzyeh Ghassemi (CHIL, 2021)

Towards Robust Classification Model by Counterfactual and Invariant Data Generation. - Chun-Hao Chang; George-Alexandru Adam; Anna Goldenberg (CVPR, 2021)

Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. - Vinith M. Suriyakumar; Nicolas Papernot; Anna Goldenberg; Marzyeh Ghassemi (FAccT, 2021)

Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding. - Sana Tonekaboni; Danny Eytan; Anna Goldenberg (ICLR, 2021)

How Interpretable and Trustworthy are GAMs? - Chun-Hao Chang; Sarah Tan; Benjamin J. Lengerich; Anna Goldenberg; Rich Caruana (KDD, 2021)

3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI. - Alex Chang; Vinith M. Suriyakumar; Abhishek Moturu; James Tu; Nipaporn Tewattanarat; Sayali Joshi; Andrea Doria 001; Anna Goldenberg (CoRR, 2021)

Extracting Clinician's Goals by What-if Interpretable Modeling. - Chun-Hao Chang; George-Alexandru Adam; Rich Caruana; Anna Goldenberg (CoRR, 2021)

Decoupling Local and Global Representations of Time Series. - Sana Tonekaboni; Chun-Liang Li; Sercan Ö. Arik; Anna Goldenberg; Tomas Pfister (AISTATS, 2022)

How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU. - Sana Tonekaboni; Gabriela Morgenshtern; Azadeh Assadi; Aslesha Pokhrel; Xi Huang; Anand Jayarajan; Robert Greer; Gennady Pekhimenko; Melissa D. McCradden; Mjaye Mazwi; Anna Goldenberg (CHIL, 2022)

Learning Unsupervised Representations for ICU Timeseries. - Addison Weatherhead; Robert Greer; Michael-Alice Moga; Mjaye Mazwi; Danny Eytan; Anna Goldenberg; Sana Tonekaboni (CHIL, 2022)

Volume-based Performance not Guaranteed by Promising Patch-based Results in Medical Imaging. - Abhishek Moturu; Sayali Joshi; Andrea S. Doria; Anna Goldenberg (ICBINB, 2022)

NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning. - Chun-Hao Chang; Rich Caruana; Anna Goldenberg (ICLR, 2022)

Barriers and opportunities to improve renal outcomes in South Africa using AI technology for pediatric ultrasound interpretation. - Lauren Erdman; Karen Milford; Zubrina Solomon; Mandy Rickard; Armando J. Lorenzo; Andrew Grieve; Anna Goldenberg (ICTD, 2022)

Error Amplification When Updating Deployed Machine Learning Models. - George-Alexandru Adam; Chun-Hao Kingsley Chang; Benjamin Haibe-Kains; Anna Goldenberg (MLHC, 2022)

Considerations for Visualizing Uncertainty in Clinical Machine Learning Models. - Caitlin F. Harrigan; Gabriela Morgenshtern; Anna Goldenberg; Fanny Chevalier (CoRR, 2022)

Time-Varying Correlation Networks for Interpretable Change Point Detection. - Kopal Garg; Sana Tonekaboni; Anna Goldenberg (CoRR, 2022)

From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Enough to Predict Obstructive Hydronephrosis. - Stanley Bryan Z. Hua; Mandy Rickard; John Weaver; Alice X. Xiang; Daniel Alvarez; Kyla N. Velear; Kunj Sheth; Gregory E. Tasian; Armando J. Lorenzo; Anna Goldenberg; Lauren Erdman (CoRR, 2022)

An integration engineering framework for machine learning in healthcare. - Azadeh Assadi; Peter C. Laussen; Andrew J. Goodwin; Sebastian Goodfellow; Will Dixon; Robert W. Greer; Anusha Jegatheeswaran; Devin Singh; Melissa D. McCradden; Sara N. Gallant; Anna Goldenberg; Danny Eytan; et al. (Frontiers Digit. Health, 2022)

The silent trial - the bridge between bench-to-bedside clinical AI applications. - Jethro C. C. Kwong; Lauren Erdman; Adree Khondker; Marta Skreta; Anna Goldenberg; Melissa D. McCradden; Armando J. Lorenzo; Mandy Rickard (Frontiers Digit. Health, 2022)

Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum. - Sarah M. Goodday; E. Karlin; A. Brooks; C. Chapman; Daniel R. Karlin; Luca Foschini 002; E. Kipping; M. Wildman; M. Francis; H. Greenman; Li Li 062; Eric E. Schadt; et al. (npj Digit. Medicine, 2022)

The promise of machine learning applications in solid organ transplantation. - Neta Gotlieb; Amirhossein Azhie; Divya Sharma; Ashley Spann; Nan-Ji Suo; Jason Tran; Ani Orchanian-Cheff; Bo Wang 044; Anna Goldenberg; Michael Chassé; Héloïse Cardinal; Joseph Paul Cohen; et al. (npj Digit. Medicine, 2022)

Childhood Adversity's Impact on Dynamic Mental Health During and Post Pregnancy. - Jennifer Yu; Mai Ali; Rui Zhu; Parinita Edke; Anna Goldenberg (DSTNDS, 2023)

What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB. - Melissa D. McCradden; Oluwadara Odusi; Shalmali Joshi; Ismail Akrout; Kagiso Ndlovu; Ben Glocker; Gabriel Maicas; Xiaoxuan Liu; Mjaye Mazwi; Tee Garnett; Lauren Oakden-Rayner; Myrtede Alfred; et al. (FAccT, 2023)

Dynamic Interpretable Change Point Detection for Physiological Data Analysis. - Jennifer Yu; Tina Behrouzi; Kopal Garg; Anna Goldenberg; Sana Tonekaboni (ML4H@NeurIPS, 2023)

Moment-alignment domain adaptation in the few-shot and low-resource context. - Lauren Erdman; Mandy Rickard; Kyla N. Velear; Daniel Alvarez; Kunj Sheth; Armando J. Lorenzo; Bo Wang 044; Anna Goldenberg (SIPAIM, 2023)

RiskFix: Supporting Expert Validation of Predictive Timeseries Models in High-Intensity Settings. - Gabriela Morgenshtern; Arnav Verma; Sana Tonekaboni; Robert Greer; Jürgen Bernard; Mjaye Mazwi; Anna Goldenberg; Fanny Chevalier (EuroVis (Short Papers), 2023)

Maintaining Stability and Plasticity for Predictive Churn Reduction. - George Adam; Benjamin Haibe-Kains; Anna Goldenberg (CoRR, 2023)

Dissecting the heterogeneity of "in the wild" stress from multimodal sensor data. - Sujay Nagaraj; Sarah M. Goodday; Thomas Hartvigsen; Adrien Boch; Kopal Garg; Sindhu C. M. Gowda; Luca Foschini 002; Marzyeh Ghassemi; Stephen H. Friend; Anna Goldenberg (npj Digit. Medicine, 2023)

Improving Identically Distributed and Out-of-Distribution Medical Image Classification with Segmentation-Guided Attention in Small Dataset Scenarios. - Mariia Rizhko; Lauren Erdman; Mandy Rickard; Kunj Sheth; Daniel Alvarez; Kyla N. Velear; Megan A. Bonnett; Christopher S. Cooper; Gregory E. Tasian; John Weaver; Alice X. Xiang; Armando J. Lorenzo; et al. (MIDL, 2024)

Towards a personalized pregnancy experience: Forecasting symptoms using graph neural networks and digital health technologies. - Rui Zhu; Jennifer Yu; Stephen H. Friend; Sarah M. Goodday; Bo Wang 044; Anna Goldenberg (ML4H@NeurIPS, 2024)

Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Sensor Data. - Sujay Nagaraj; Andrew J. Goodwin; Dmytro Lopushanskyy; Sebastian D. Goodfellow; Danny Eytan; Hadrian Balaci; Robert Greer; Anand Jayarajan; Azadeh Assadi; Mjaye Leslie Mazwi; Anna Goldenberg (MLHC, 2024)

Integrate Any Omics: Towards genome-wide data integration for patient stratification. - Shihao Ma; Andy G. X. Zeng; Benjamin Haibe-Kains; Anna Goldenberg; John E. Dick; Bo Wang 044 (CoRR, 2024)

Learning from Time Series under Temporal Label Noise. - Sujay Nagaraj; Walter Gerych; Sana Tonekaboni; Anna Goldenberg; Berk Ustun; Thomas Hartvigsen (CoRR, 2024)

Measurement Scheduling for ICU Patients with Offline Reinforcement Learning. - Zongliang Ji; Anna Goldenberg; Rahul G. Krishnan (CoRR, 2024)

Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Waveform Data. - Sujay Nagaraj; Andrew J. Goodwin; Dmytro Lopushanskyy; Danny Eytan; Robert W. Greer; Sebastian D. Goodfellow; Azadeh Assadi; Anand Jayarajan; Anna Goldenberg; Mjaye L. Mazwi (CoRR, 2024)

ExOSITO: Explainable Off-Policy Learning with Side Information for Intensive Care Unit Blood Test Orders. - Zongliang Ji; Andre Carlos Kajdacsy-Balla Amaral; Anna Goldenberg; Rahul G. Krishnan (CHIL, 2025)

Learning under Temporal Label Noise. - Sujay Nagaraj; Walter Gerych; Sana Tonekaboni; Anna Goldenberg; Berk Ustun; Thomas Hartvigsen (ICLR, 2025)

HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery. - Sana Tonekaboni; Tina Behrouzi; Addison Weatherhead; Emily B. Fox; David M. Blei; Anna Goldenberg (UAI, 2025)

Moving towards genome-wide data integration for patient stratification with Integrate Any Omics. - Shihao Ma; Andy G. X. Zeng; Benjamin Haibe-Kains; Anna Goldenberg; John E. Dick; Bo Wang 044 (Nat. Mac. Intell., 2025)

DynaSubVAE: Adaptive Subgrouping for Scalable and Robust OOD Detection. - Tina Behrouzi; Sana Tonekaboni; Rahul G. Krishnan; Anna Goldenberg (CoRR, 2025)

Impute With Confidence: A Framework for Uncertainty Aware Multivariate Time Series Imputation. - Addison Weatherhead; Anna Goldenberg (CoRR, 2025)