Goldenberg, Anna

28 publications

CHIL 2025 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

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

ICLR 2025 Learning Under Temporal Label Noise Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen

MIDL 2024 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 Velaer, Megan A. Bonnett, Christopher S. Cooper, Gregory E. Tasian, John Weaver, Alice Xiang, Armando J. Lorenzo, Anna Goldenberg

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

NeurIPSW 2024 Time Series Under Temporal Label Noise Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen

NeurIPSW 2023 CongFu: Conditional Graph Fusion for Drug Synergy Prediction Oleksii Tsepa, Bohdan Naida, Anna Goldenberg, Bo Wang

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

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

NeurIPSW 2022 Feature Restricted Group Dropout for Robust Electronic Health Record Predictions Bret Nestor, Anna Goldenberg, Marzyeh Ghassemi

CHIL 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 McCradden, Fanny Chevalier, 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

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

NeurIPSW 2022 Volume-Based Performance Not Guaranteed by Promising Patch-Based Results in Medical Imaging Abhishek Moturu, Sayali Joshi, Andrea S. Doria, Anna Goldenberg

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

ICLR 2021 Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding Sana Tonekaboni, Danny Eytan, Anna Goldenberg

MLHC 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, Chloe Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg, Marzyeh Ghassemi

NeurIPS 2020 What Went Wrong and When? Instance-Wise Feature Importance for Time-Series Black-Box Models Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David K. Duvenaud, Anna Goldenberg

ICML 2019 Dynamic Measurement Scheduling for Event Forecasting Using Deep RL Chun-Hao Chang, Mingjie Mai, Anna Goldenberg

ICLR 2019 Explaining Image Classifiers by Counterfactual Generation Chun-Hao Chang, Elliot Creager, Anna Goldenberg, David Duvenaud

MLHC 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 2018 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 Goodwin, Michael Brudno, Anna Goldenberg

FnTML 2009 A Survey of Statistical Network Models Anna Goldenberg, Alice X. Zheng, Stephen E. Fienberg, Edoardo M. Airoldi

ICML 2006 Exploratory Study of a New Model for Evolving Networks Anna Goldenberg, Alice X. Zheng

ICML 2006 Statistical Network Analysis: Models, Issues, and New Directions - ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected Papers Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Anna Goldenberg, Eric P. Xing, Alice X. Zheng

ICML 2004 Tractable Learning of Large Bayes Net Structures from Sparse Data Anna Goldenberg, Andrew W. Moore