Anna Goldenberg

99 papers A* 8A 2C 1Misc 1Journal 62Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Can we generate portable representations for clinical time series data using LLMs? CoRR Zongliang Ji, Yifei Sun, André Amaral, Anna Goldenberg, Rahul G. Krishnan
2026	J	`jnl`	Dialogue to Question Generation for Evidence-based Medical Guideline Agent Development. CoRR Zongliang Ji, Ziyang Zhang, Xincheng Tan, Matthew Thompson, Anna Goldenberg, Carl Yang, Rahul G. Krishnan, Fan Zhang
2025	J	`jnl`	DynaSubVAE: Adaptive Subgrouping for Scalable and Robust OOD Detection. CoRR Tina Behrouzi, Sana Tonekaboni, Rahul G. Krishnan, Anna Goldenberg
2025	—	`conf`	ExOSITO: Explainable Off-Policy Learning with Side Information for Intensive Care Unit Blood Test Orders. CHIL Zongliang Ji, Andre Carlos Kajdacsy-Balla Amaral, Anna Goldenberg, Rahul G. Krishnan
2025	J	`jnl`	ExOSITO: Explainable Off-Policy Learning with Side Information for Intensive Care Unit Blood Test Orders. CoRR Zongliang Ji, Andre Carlos Kajdacsy-Balla Amaral, Anna Goldenberg, Rahul G. Krishnan
2025	A	`conf`	HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery. UAI Sana Tonekaboni, Tina Behrouzi, Addison Weatherhead, Emily B. Fox, David M. Blei, Anna Goldenberg
2025	J	`jnl`	Impute With Confidence: A Framework for Uncertainty Aware Multivariate Time Series Imputation. CoRR Addison Weatherhead, Anna Goldenberg
2025	A*	`conf`	Learning under Temporal Label Noise. ICLR Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen
2025	J	`jnl`	LiLAW: Lightweight Learnable Adaptive Weighting to Meta-Learn Sample Difficulty and Improve Noisy Training. CoRR Abhishek Moturu, Anna Goldenberg, Babak Taati
2025	J	`jnl`	Moving towards genome-wide data integration for patient stratification with Integrate Any Omics. Nat. Mac. Intell. Shihao Ma, Andy G. X. Zeng, Benjamin Haibe-Kains, Anna Goldenberg, John E. Dick, Bo Wang
2024	—	`conf`	Improving Identically Distributed and Out-of-Distribution Medical Image Classification with Segmentation-Guided Attention in Small Dataset Scenarios. MIDL 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, Anna Goldenberg
2024	J	`jnl`	Integrate Any Omics: Towards genome-wide data integration for patient stratification. CoRR Shihao Ma, Andy G. X. Zeng, Benjamin Haibe-Kains, Anna Goldenberg, John E. Dick, Bo Wang
2024	J	`jnl`	Learning from Time Series under Temporal Label Noise. CoRR Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen
2024	J	`jnl`	Measurement Scheduling for ICU Patients with Offline Reinforcement Learning. CoRR Zongliang Ji, Anna Goldenberg, Rahul G. Krishnan
2024	—	`conf`	Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Sensor Data. MLHC 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
2024	J	`jnl`	Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Waveform Data. CoRR Sujay Nagaraj, Andrew J. Goodwin, Dmytro Lopushanskyy, Danny Eytan, Robert W. Greer, Sebastian D. Goodfellow, Azadeh Assadi, Anand Jayarajan, Anna Goldenberg, Mjaye L. Mazwi
2024	—	`conf`	Towards a personalized pregnancy experience: Forecasting symptoms using graph neural networks and digital health technologies. ML4H@NeurIPS Rui Zhu, Jennifer Yu, Stephen H. Friend, Sarah M. Goodday, Bo Wang, Anna Goldenberg
2023	—	`conf`	Childhood Adversity's Impact on Dynamic Mental Health During and Post Pregnancy. DSTNDS Jennifer Yu, Mai Ali, Rui Zhu, Parinita Edke, Anna Goldenberg
2023	J	`jnl`	Dissecting the heterogeneity of "in the wild" stress from multimodal sensor data. npj Digit. Medicine Sujay Nagaraj, Sarah M. Goodday, Thomas Hartvigsen, Adrien Boch, Kopal Garg, Sindhu C. M. Gowda, Luca Foschini, Marzyeh Ghassemi, Stephen H. Friend, Anna Goldenberg
2023	—	`conf`	Dynamic Interpretable Change Point Detection for Physiological Data Analysis. ML4H@NeurIPS Jennifer Yu, Tina Behrouzi, Kopal Garg, Anna Goldenberg, Sana Tonekaboni
2023	J	`jnl`	Maintaining Stability and Plasticity for Predictive Churn Reduction. CoRR George Adam, Benjamin Haibe-Kains, Anna Goldenberg
2023	—	`conf`	Moment-alignment domain adaptation in the few-shot and low-resource context. SIPAIM Lauren Erdman, Mandy Rickard, Kyla N. Velear, Daniel Alvarez, Kunj Sheth, Armando J. Lorenzo, Bo Wang, Anna Goldenberg
2023	—	`conf`	RiskFix: Supporting Expert Validation of Predictive Timeseries Models in High-Intensity Settings. EuroVis (Short Papers) Gabriela Morgenshtern, Arnav Verma, Sana Tonekaboni, Robert Greer, Jürgen Bernard, Mjaye Mazwi, Anna Goldenberg, Fanny Chevalier
2023	—	`conf`	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 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
2022	J	`jnl`	An integration engineering framework for machine learning in healthcare. Frontiers Digit. Health 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
2022	C	`conf`	Barriers and opportunities to improve renal outcomes in South Africa using AI technology for pediatric ultrasound interpretation. ICTD Lauren Erdman, Karen Milford, Zubrina Solomon, Mandy Rickard, Armando J. Lorenzo, Andrew Grieve, Anna Goldenberg
2022	J	`jnl`	Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum. npj Digit. Medicine 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, Nick Taptiklis, Corey Centen, S. Smith, Stephen H. Friend
2022	J	`jnl`	Considerations for Visualizing Uncertainty in Clinical Machine Learning Models. CoRR Caitlin F. Harrigan, Gabriela Morgenshtern, Anna Goldenberg, Fanny Chevalier
2022	A	`conf`	Decoupling Local and Global Representations of Time Series. AISTATS Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister
2022	J	`jnl`	Decoupling Local and Global Representations of Time Series. CoRR Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister
2022	—	`conf`	Error Amplification When Updating Deployed Machine Learning Models. MLHC George-Alexandru Adam, Chun-Hao Kingsley Chang, Benjamin Haibe-Kains, Anna Goldenberg
2022	J	`jnl`	From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Enough to Predict Obstructive Hydronephrosis. CoRR 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
2022	—	`conf`	How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU. CHIL Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg
2022	—	`conf`	Learning Unsupervised Representations for ICU Timeseries. CHIL Addison Weatherhead, Robert Greer, Michael-Alice Moga, Mjaye Mazwi, Danny Eytan, Anna Goldenberg, Sana Tonekaboni
2022	A*	`conf`	NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning. ICLR Chun-Hao Chang, Rich Caruana, Anna Goldenberg
2022	J	`jnl`	The promise of machine learning applications in solid organ transplantation. npj Digit. Medicine 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
2022	J	`jnl`	The silent trial - the bridge between bench-to-bedside clinical AI applications. Frontiers Digit. Health Jethro C. C. Kwong, Lauren Erdman, Adree Khondker, Marta Skreta, Anna Goldenberg, Melissa D. McCradden, Armando J. Lorenzo, Mandy Rickard
2022	J	`jnl`	Time-Varying Correlation Networks for Interpretable Change Point Detection. CoRR Kopal Garg, Sana Tonekaboni, Anna Goldenberg
2022	—	`conf`	Volume-based Performance not Guaranteed by Promising Patch-based Results in Medical Imaging. ICBINB Abhishek Moturu, Sayali Joshi, Andrea S. Doria, Anna Goldenberg
2021	J	`jnl`	3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI. CoRR Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, James Tu, Nipaporn Tewattanarat, Sayali Joshi, Andrea Doria, Anna Goldenberg
2021	—	`conf`	A comprehensive EHR timeseries pre-training benchmark. CHIL Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
2021	—	`conf`	Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. FAccT Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
2021	J	`jnl`	Extracting Clinician's Goals by What-if Interpretable Modeling. CoRR Chun-Hao Chang, George-Alexandru Adam, Rich Caruana, Anna Goldenberg
2021	A*	`conf`	How Interpretable and Trustworthy are GAMs? KDD Chun-Hao Chang, Sarah Tan, Benjamin J. Lengerich, Anna Goldenberg, Rich Caruana
2021	J	`jnl`	NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning. CoRR Chun-Hao Chang, Rich Caruana, Anna Goldenberg
2021	A*	`conf`	Towards Robust Classification Model by Counterfactual and Invariant Data Generation. CVPR Chun-Hao Chang, George-Alexandru Adam, Anna Goldenberg
2021	J	`jnl`	Towards Robust Classification Model by Counterfactual and Invariant Data Generation. CoRR Chun-Hao Chang, George-Alexandru Adam, Anna Goldenberg
2021	A*	`conf`	Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding. ICLR Sana Tonekaboni, Danny Eytan, Anna Goldenberg
2021	J	`jnl`	Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding. CoRR Sana Tonekaboni, Danny Eytan, Anna Goldenberg
2020	J	`jnl`	A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. CoRR Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
2020	J	`jnl`	Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. CoRR Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
2020	J	`jnl`	Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds. CoRR Erik Drysdale, Devin Singh, Anna Goldenberg
2020	—	`conf`	Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation. MLHC George-Alexandru Adam, Chun-Hao Kingsley Chang, Benjamin Haibe-Kains, Anna Goldenberg
2020	J	`jnl`	How Interpretable and Trustworthy are GAMs? CoRR Chun-Hao Chang, Sarah Tan, Benjamin J. Lengerich, Anna Goldenberg, Rich Caruana
2020	J	`jnl`	Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. J. Am. Medical Informatics Assoc. Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Mjaye Mazwi, Anna Goldenberg, Randi Zlotnik Shaul
2020	—	`conf`	Predicting Obstructive Hydronephrosis Based on Ultrasound Alone. MICCAI (3) Lauren Erdman, Marta Skreta, Mandy Rickard, Carson McLean, Aziz Mezlini, Daniel T. Keefe, Anne-Sophie Blais, Michael Brudno, Armando J. Lorenzo, Anna Goldenberg
2020	—	`conf`	Preparing a Clinical Support Model for Silent Mode in General Internal Medicine. MLHC Bret Nestor, Liam G. McCoy, Amol Verma, Chloé Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg, Marzyeh Ghassemi
2020	J	`jnl`	Using Generative Models for Pediatric wbMRI. CoRR Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, Nipaporn Tewattanarat, Andrea Doria, Anna Goldenberg
2020	J	`jnl`	What went wrong and when? Instance-wise Feature Importance for Time-series Models. CoRR Sana Tonekaboni, Shalmali Joshi, David Duvenaud, Anna Goldenberg
2020	A*	`conf`	What went wrong and when? Instance-wise feature importance for time-series black-box models. NeurIPS Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David Duvenaud, Anna Goldenberg
2019	J	`jnl`	Dr.VAE: improving drug response prediction via modeling of drug perturbation effects. Bioinform. Ladislav Rampásek, Daniel Hidru, Petr Smirnov, Benjamin Haibe-Kains, Anna Goldenberg
2019	A*	`conf`	Dynamic Measurement Scheduling for Event Forecasting using Deep RL. ICML Chun-Hao Chang, Mingjie Mai, Anna Goldenberg
2019	J	`jnl`	Dynamic Measurement Scheduling for Event Forecasting using Deep RL. CoRR Chun-Hao Chang, Mingjie Mai, Anna Goldenberg
2019	—	`conf`	Explaining Image Classifiers by Counterfactual Generation. ICLR (Poster) Chun-Hao Chang, Elliot Creager, Anna Goldenberg, David Duvenaud
2019	—	`conf`	Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. MLHC Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2019	J	`jnl`	Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. CoRR Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2019	J	`jnl`	Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities. Inf. Fusion Marinka Zitnik, Francis Nguyen, Bo Wang, Jure Leskovec, Anna Goldenberg, Michael M. Hoffman
2019	J	`jnl`	Reducing Adversarial Example Transferability Using Gradient Regularization. CoRR George Adam, Petr Smirnov, Benjamin Haibe-Kains, Anna Goldenberg
2019	J	`jnl`	The False Positive Control Lasso. CoRR Erik Drysdale, Yingwei Peng, Timothy P. Hanna, Paul Nguyen, Anna Goldenberg
2019	—	`conf`	What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. MLHC Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
2019	J	`jnl`	What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. CoRR Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
2018	J	`jnl`	Dynamic Measurement Scheduling for Adverse Event Forecasting using Deep RL. CoRR Chun-Hao Chang, Mingjie Mai, Anna Goldenberg
2018	J	`jnl`	Explaining Image Classifiers by Adaptive Dropout and Generative In-filling. CoRR Chun-Hao Chang, Elliot Creager, Anna Goldenberg, David Duvenaud
2018	J	`jnl`	Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities. CoRR Marinka Zitnik, Francis Nguyen, Bo Wang, Jure Leskovec, Anna Goldenberg, Michael M. Hoffman
2018	—	`conf`	Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU. MLHC Sana Tonekaboni, Mjaye Mazwi, Peter Laussen, Danny Eytan, Robert Greer, Sebastian D. Goodfellow, Andrew J. Goodwin, Michael Brudno, Anna Goldenberg
2018	J	`jnl`	Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. CoRR Bret Nestor, Matthew B. A. McDermott, Geeticka Chauhan, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2018	J	`jnl`	Stochastic Combinatorial Ensembles for Defending Against Adversarial Examples. CoRR George-Alexandru Adam, Petr Smirnov, Anna Goldenberg, David Duvenaud, Benjamin Haibe-Kains
2017	J	`jnl`	Dropout Feature Ranking for Deep Learning Models. CoRR Chun-Hao Chang, Ladislav Rampásek, Anna Goldenberg
2017	J	`jnl`	Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases. PLoS Comput. Biol. Aziz M. Mezlini, Anna Goldenberg
2017	J	`jnl`	Vicus: Exploiting local structures to improve network-based analysis of biological data. PLoS Comput. Biol. Bo Wang, Lin Huang, Yuke Zhu, Anshul Kundaje, Serafim Batzoglou, Anna Goldenberg
2016	J	`jnl`	JBASE: Joint Bayesian Analysis of Subphenotypes and Epistasis. Bioinform. 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
2016	J	`jnl`	Modeling trajectories of mental health: challenges and opportunities. CoRR 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
2016	J	`jnl`	PharmacoGx: an R package for analysis of large pharmacogenomic datasets. Bioinform. Petr Smirnov, Zhaleh Safikhani, Nehme Hachem, Dong Wang, Adrian She, Catharina Olsen, Mark Freeman, Heather Marie Selby, Deena M. A. Gendoo, Patrick Grossmann, Andrew H. Beck, Hugo J. W. L. Aerts, Mathieu Lupien, Anna Goldenberg, Benjamin Haibe-Kains
2016	J	`jnl`	Safikhani Nat. 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
2015	J	`jnl`	Combining exome and gene expression datasets in one graphical model of disease to empower the discovery of disease mechanisms. CoRR Aziz M. Mezlini, Fabio Fuligni, Adam Shlien, Anna Goldenberg
2015	J	`jnl`	Subtyping: What It is and Its Role in Precision Medicine. IEEE Intell. Syst. Suchi Saria, Anna Goldenberg
2014	J	`jnl`	A probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information. Bioinform. Yue Li, Anna Goldenberg, Ka-Chun Wong, Zhaolei Zhang
2014	J	`jnl`	EquiNMF: Graph Regularized Multiview Nonnegative Matrix Factorization. CoRR Daniel Hidru, Anna Goldenberg
2014	J	`jnl`	Gradient-based Laplacian Feature Selection. CoRR Bo Wang, Anna Goldenberg
2012	J	`jnl`	Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study. BMC Syst. Biol. Mohammed Alshalalfa, Gary D. Bader, Anna Goldenberg, Quaid Morris, Reda Alhajj
2012	Misc	`conf`	Mixture Model for Sub-Phenotyping in GWAS. Pacific Symposium on Biocomputing David Warde-Farley, Michael Brudno, Quaid Morris, Anna Goldenberg
2011	J	`jnl`	Unsupervised detection of genes of influence in lung cancer using biological networks. Bioinform. Anna Goldenberg, Sara Mostafavi, Gerald T. Quon, Paul C. Boutros, Quaid Morris
2009	J	`jnl`	A Survey of Statistical Network Models. Found. Trends Mach. Learn. Anna Goldenberg, Alice X. Zheng, Stephen E. Fienberg, Edoardo M. Airoldi
2009	J	`jnl`	A survey of statistical network models. CoRR Anna Goldenberg, Alice X. Zheng, Stephen E. Fienberg, Edoardo M. Airoldi
2007	—	`ed.`	Statistical Network Analysis: Models, Issues, and New Directions - ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected Papers SNA@ICML Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Anna Goldenberg, Eric P. Xing, Alice X. Zheng
2006	—	`conf`	Exploratory Study of a New Model for Evolving Networks. SNA@ICML Anna Goldenberg, Alice X. Zheng
2005	—	`conf`	Bayes net graphs to understand co-authorship networks? LinkKDD Anna Goldenberg, Andrew W. Moore
2004	A*	`conf`	Tractable learning of large Bayes net structures from sparse data. ICML Anna Goldenberg, Andrew W. Moore
2001	J	`jnl`	Artificial neural network approach to data analysis and parameter estimation in experimental spectroscopy. Informatica (Slovenia) Mehmed M. Kantardzic, Anna Goldenberg, Troy E. Howe, Peter Faguy