Anna Goldenberg

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 70

Top Topics

Change Point Detection

Bayesian Analysis

Top Venues

Publications

Shihao Ma, Andy G. X. Zeng, Benjamin Haibe-Kains, Anna Goldenberg, John E. Dick, Bo Wang
Integrate Any Omics: Towards genome-wide data integration for patient stratification. CoRR (2024)
Zongliang Ji, Anna Goldenberg, Rahul G. Krishnan
Measurement Scheduling for ICU Patients with Offline Reinforcement Learning. CoRR (2024)
Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen
Learning from Time Series under Temporal Label Noise. CoRR (2024)
Jennifer Yu, Tina Behrouzi, Kopal Garg, Anna Goldenberg, Sana Tonekaboni
Dynamic Interpretable Change Point Detection for Physiological Data Analysis. ML4H@NeurIPS (2023)
Lauren Erdman, Mandy Rickard, Kyla N. Velear, Daniel Alvarez, Kunj Sheth, Armando J. Lorenzo, Bo Wang, Anna Goldenberg
Moment-alignment domain adaptation in the few-shot and low-resource context. SIPAIM (2023)
Gabriela Morgenshtern, Arnav Verma, Sana Tonekaboni, Robert Greer, Jürgen Bernard, Mjaye Mazwi, Anna Goldenberg, Fanny Chevalier
RiskFix: Supporting Expert Validation of Predictive Timeseries Models in High-Intensity Settings. EuroVis (Short Papers) (2023)
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, Irvine Sihlahla, Oswa Shafei, Anna Goldenberg
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. FAccT (2023)
Jennifer Yu, Mai Ali, Rui Zhu, Parinita Edke, Anna Goldenberg
Childhood Adversity's Impact on Dynamic Mental Health During and Post Pregnancy. DSTNDS (2023)
George Adam, Benjamin Haibe-Kains, Anna Goldenberg
Maintaining Stability and Plasticity for Predictive Churn Reduction. CoRR (2023)
Abhishek Moturu, Sayali Joshi, Andrea S. Doria, Anna Goldenberg
Volume-based Performance not Guaranteed by Promising Patch-based Results in Medical Imaging. ICBINB (2022)
Neta Gotlieb, Amirhossein Azhie, Divya Sharma, Ashley Spann, Nan-Ji Suo, Jason Tran, Ani Orchanian-Cheff, Bo Wang, Anna Goldenberg, Michael Chassé, Héloïse Cardinal, Joseph Paul Cohen, Andrea Lodi, Melanie Dieude, Mamatha Bhat
The promise of machine learning applications in solid organ transplantation. npj Digit. Medicine 5 (2022)
Chun-Hao Chang, Rich Caruana, Anna Goldenberg
NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning. ICLR (2022)
Sarah M. Goodday, E. Karlin, A. Brooks, C. Chapman, Daniel R. Karlin, Luca Foschini, E. Kipping, M. Wildman, M. Francis, H. Greenman, Li Li, Eric E. Schadt, Marzyeh Ghassemi, Anna Goldenberg, Francesca Cormack, N. Taptiklis, C. Centen, S. Smith, Stephen H. Friend
Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum. npj Digit. Medicine 5 (2022)
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, Mjaye L. Mazwi
An integration engineering framework for machine learning in healthcare. Frontiers Digit. Health 4 (2022)
Jethro C. C. Kwong, Lauren Erdman, Adree Khondker, Marta Skreta, Anna Goldenberg, Melissa D. McCradden, Armando J. Lorenzo, Mandy Rickard
The silent trial - the bridge between bench-to-bedside clinical AI applications. Frontiers Digit. Health 4 (2022)
Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister
Decoupling Local and Global Representations of Time Series. CoRR (2022)
Kopal Garg, Sana Tonekaboni, Anna Goldenberg
Time-Varying Correlation Networks for Interpretable Change Point Detection. CoRR (2022)
Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg
How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU. CHIL (2022)
Stanley Bryan Z. Hua, Mandy Rickard, John Weaver, Alice X. Xiang, Daniel Alvarez, Kyla N. Velear, Kunj Sheth, Gregory E. Tasian, Armando Lorenzo, Anna Goldenberg, Lauren Erdman
From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Enough to Predict Obstructive Hydronephrosis. CoRR (2022)
Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister
Decoupling Local and Global Representations of Time Series. AISTATS (2022)
Addison Weatherhead, Robert Greer, Michael-Alice Moga, Mjaye Mazwi, Danny Eytan, Anna Goldenberg, Sana Tonekaboni
Learning Unsupervised Representations for ICU Timeseries. CHIL (2022)
George-Alexandru Adam, Chun-Hao Kingsley Chang, Benjamin Haibe-Kains, Anna Goldenberg
Error Amplification When Updating Deployed Machine Learning Models. MLHC (2022)
Caitlin F. Harrigan, Gabriela Morgenshtern, Anna Goldenberg, Fanny Chevalier
Considerations for Visualizing Uncertainty in Clinical Machine Learning Models. CoRR (2022)
Chun-Hao Chang, Sarah Tan, Benjamin Lengerich, Anna Goldenberg, Rich Caruana
How Interpretable and Trustworthy are GAMs? KDD (2021)
Chun-Hao Chang, George-Alexandru Adam, Rich Caruana, Anna Goldenberg
Extracting Clinician's Goals by What-if Interpretable Modeling. CoRR (2021)
Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
A comprehensive EHR timeseries pre-training benchmark. CHIL (2021)
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding. ICLR (2021)
Chun-Hao Chang, Rich Caruana, Anna Goldenberg
NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning. CoRR (2021)
Chun-Hao Chang, George-Alexandru Adam, Anna Goldenberg
Towards Robust Classification Model by Counterfactual and Invariant Data Generation. CoRR (2021)
Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, James Tu, Nipaporn Tewattanarat, Sayali Joshi, Andrea Doria, Anna Goldenberg
3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI. CoRR (2021)
Chun-Hao Chang, George-Alexandru Adam, Anna Goldenberg
Towards Robust Classification Model by Counterfactual and Invariant Data Generation. CVPR (2021)
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding. CoRR (2021)
Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. FAccT (2021)
Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David Duvenaud, Anna Goldenberg
What went wrong and when? Instance-wise feature importance for time-series black-box models. NeurIPS (2020)
Lauren Erdman, Marta Skreta, Mandy Rickard, Carson McLean, Aziz Mezlini, Daniel T. Keefe, Anne-Sophie Blais, Michael Brudno, Armando Lorenzo, Anna Goldenberg
Predicting Obstructive Hydronephrosis Based on Ultrasound Alone. MICCAI (3) (2020)
Bret Nestor, Liam G. McCoy, Amol Verma, Chloé Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg, Marzyeh Ghassemi
Preparing a Clinical Support Model for Silent Mode in General Internal Medicine. MLHC (2020)
Sana Tonekaboni, Shalmali Joshi, David Duvenaud, Anna Goldenberg
What went wrong and when? Instance-wise Feature Importance for Time-series Models. CoRR (2020)
Chun-Hao Chang, Sarah Tan, Benjamin Lengerich, Anna Goldenberg, Rich Caruana
How Interpretable and Trustworthy are GAMs? CoRR (2020)
Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. CoRR (2020)
Erik Drysdale, Devin Singh, Anna Goldenberg
Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds. CoRR (2020)
Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. CoRR (2020)
Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, Nipaporn Tewattanarat, Andrea Doria, Anna Goldenberg
Using Generative Models for Pediatric wbMRI. CoRR (2020)
George-Alexandru Adam, Chun-Hao Kingsley Chang, Benjamin Haibe-Kains, Anna Goldenberg
Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation. MLHC (2020)
Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Mjaye Mazwi, Anna Goldenberg, Randi Zlotnik Shaul
Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. J. Am. Medical Informatics Assoc. 27 (12) (2020)
Chun-Hao Chang, Mingjie Mai, Anna Goldenberg
Dynamic Measurement Scheduling for Event Forecasting using Deep RL. ICML (2019)
Chun-Hao Chang, Elliot Creager, Anna Goldenberg, David Duvenaud
Explaining Image Classifiers by Counterfactual Generation. ICLR (Poster) (2019)
Erik Drysdale, Yingwei Peng, Timothy P. Hanna, Paul Nguyen, Anna Goldenberg
The False Positive Control Lasso. CoRR (2019)
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. CoRR (2019)
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. MLHC (2019)
Ladislav Rampásek, Daniel Hidru, Petr Smirnov, Benjamin Haibe-Kains, Anna Goldenberg
Dr.VAE: improving drug response prediction via modeling of drug perturbation effects. Bioinform. 35 (19) (2019)
Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. MLHC (2019)
Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. CoRR (2019)
George Adam, Petr Smirnov, Benjamin Haibe-Kains, Anna Goldenberg
Reducing Adversarial Example Transferability Using Gradient Regularization. CoRR (2019)
Chun-Hao Chang, Mingjie Mai, Anna Goldenberg
Dynamic Measurement Scheduling for Event Forecasting using Deep RL. CoRR (2019)
Marinka Zitnik, Francis Nguyen, Bo Wang, Jure Leskovec, Anna Goldenberg, Michael M. Hoffman
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities. Inf. Fusion 50 (2019)
Marinka Zitnik, Francis Nguyen, Bo Wang, Jure Leskovec, Anna Goldenberg, Michael M. Hoffman
Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities. CoRR (2018)
Chun-Hao Chang, Elliot Creager, Anna Goldenberg, David Duvenaud
Explaining Image Classifiers by Adaptive Dropout and Generative In-filling. CoRR (2018)
Sana Tonekaboni, Mjaye Mazwi, Peter Laussen, Danny Eytan, Robert Greer, Sebastian D. Goodfellow, Andrew J. Goodwin, Michael Brudno, Anna Goldenberg
Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU. MLHC (2018)
Chun-Hao Chang, Mingjie Mai, Anna Goldenberg
Dynamic Measurement Scheduling for Adverse Event Forecasting using Deep RL. CoRR (2018)
George-Alexandru Adam, Petr Smirnov, Anna Goldenberg, David Duvenaud, Benjamin Haibe-Kains
Stochastic Combinatorial Ensembles for Defending Against Adversarial Examples. CoRR (2018)
Bret Nestor, Matthew B. A. McDermott, Geeticka Chauhan, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. CoRR (2018)
Chun-Hao Chang, Ladislav Rampásek, Anna Goldenberg
Dropout Feature Ranking for Deep Learning Models. CoRR (2017)
Bo Wang, Lin Huang, Yuke Zhu, Anshul Kundaje, Serafim Batzoglou, Anna Goldenberg
Vicus: Exploiting local structures to improve network-based analysis of biological data. PLoS Comput. Biol. 13 (10) (2017)
Aziz M. Mezlini, Anna Goldenberg
Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases. PLoS Comput. Biol. 13 (10) (2017)
Petr Smirnov, Zhaleh Safikhani, Nehme Hachem, Dong Wang, Adrian She, Catharina Olsen, Mark Freeman, Heather Selby, Deena M. A. Gendoo, Patrick Grossmann, Andrew H. Beck, Hugo J. W. L. Aerts, Mathieu Lupien, Anna Goldenberg, Benjamin Haibe-Kains
PharmacoGx: an R package for analysis of large pharmacogenomic datasets. Bioinform. 32 (8) (2016)
Zhaleh Safikhani, Nehme Hachem, Petr Smirnov, Mark Freeman, Anna Goldenberg, Nicolai J. Birkbak, Andrew H. Beck, Hugo J. W. L. Aerts, John Quackenbush, Benjamin Haibe-Kains
. reply. Nat. 540 (7631) (2016)
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, Anna Goldenberg
Modeling trajectories of mental health: challenges and opportunities. CoRR (2016)
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
JBASE: Joint Bayesian Analysis of Subphenotypes and Epistasis. Bioinform. 32 (2) (2016)
Suchi Saria, Anna Goldenberg
Subtyping: What It is and Its Role in Precision Medicine. IEEE Intell. Syst. 30 (4) (2015)
Aziz M. Mezlini, Fabio Fuligni, Adam Shlien, Anna Goldenberg
Combining exome and gene expression datasets in one graphical model of disease to empower the discovery of disease mechanisms. CoRR (2015)
Daniel Hidru, Anna Goldenberg
EquiNMF: Graph Regularized Multiview Nonnegative Matrix Factorization. CoRR (2014)
Bo Wang, Anna Goldenberg
Gradient-based Laplacian Feature Selection. CoRR (2014)
Yue Li, Anna Goldenberg, Ka-Chun Wong, Zhaolei Zhang
A probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information. Bioinform. 30 (5) (2014)
David Warde-Farley, Michael Brudno, Quaid Morris, Anna Goldenberg
Mixture Model for Sub-Phenotyping in GWAS. Pacific Symposium on Biocomputing (2012)
Mohammed Alshalalfa, Gary D. Bader, Anna Goldenberg, Quaid Morris, Reda Alhajj
Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study. BMC Syst. Biol. 6 (2012)
Anna Goldenberg, Sara Mostafavi, Gerald T. Quon, Paul C. Boutros, Quaid Morris
Unsupervised detection of genes of influence in lung cancer using biological networks. Bioinform. 27 (22) (2011)
Anna Goldenberg, Alice X. Zheng, Stephen E. Fienberg, Edoardo M. Airoldi
A survey of statistical network models. CoRR (2009)
Anna Goldenberg, Alice X. Zheng, Stephen E. Fienberg, Edoardo M. Airoldi
A Survey of Statistical Network Models. Found. Trends Mach. Learn. 2 (2) (2009)
Anna Goldenberg, Alice X. Zheng
Exploratory Study of a New Model for Evolving Networks. SNA@ICML (2006)
Anna Goldenberg, Andrew W. Moore
Bayes net graphs to understand co-authorship networks? LinkKDD (2005)
Anna Goldenberg, Andrew W. Moore
Tractable learning of large Bayes net structures from sparse data. ICML (2004)
Mehmed M. Kantardzic, Anna Goldenberg, Troy E. Howe, Peter Faguy
Artificial neural network approach to data analysis and parameter estimation in experimental spectroscopy. Informatica (Slovenia) 25 (1) (2001)