Katherine A. Heller

According to our database, Katherine A. Heller authored at least 72 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Nteasee: A mixed methods study of expert and general population perspectives on deploying AI for health in African countries.

Mercy Nyamewaa Asiedu, Iskandar Haykel, Awa Dieng, Kerrie Kauer, Tousif Ahmed, Florence Ofori, Charisma Chan, Stephen Pfohl, Negar Rostamzadeh, Katherine A. Heller

CoRR, 2024

Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases.

Mercy Nyamewaa Asiedu, Nenad Tomasev, Chintan Ghate, Tiya Tiyasirichokchai, Awa Dieng, Oluwatosin Akande, Geoffrey Siwo, Steve Adudans, Sylvanus Aitkins, Odianosen Ehiakhamen, Eric Ndombi, Katherine A. Heller

CoRR, 2024

Development and Validation of a Deep-Learning Model for Differential Treatment Benefit Prediction for Adults with Major Depressive Disorder Deployed in the Artificial Intelligence in Depression Medication Enhancement (AIDME) Study.

David Benrimoh, Caitrin Armstrong, Joseph Mehltretter, Robert Fratila, Kelly Perlman, Sonia Israel, Adam Kapelner, Sagar V. Parikh, Jordan F. Karp, Katherine A. Heller, Gustavo Turecki

CoRR, 2024

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models.

Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres, Darlene Neal, Mercy Nyamewaa Asiedu, Awa Dieng, Nenad Tomasev, Qazi Mamunur Rashid, Shekoofeh Azizi, Negar Rostamzadeh, Liam G. McCoy, Leo Anthony Celi, Yun Liu, Mike Schaekermann, Alanna Walton, Alicia Parrish, Chirag Nagpal, Preeti Singh, Akeiylah Dewitt, Philip Andrew Mansfield, Sushant Prakash, Katherine A. Heller, Alan Karthikesalingam, Christopher Semturs, Joelle K. Barral, Greg Corrado, Yossi Matias, Jamila Smith-Loud, Ivor Horn, Karan Singhal

CoRR, 2024

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering.

Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine A. Heller, Subhrajit Roy

Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa.

Mercy Nyamewaa Asiedu, Awa Dieng, Iskandar Haykel, Negar Rostamzadeh, Stephen Pfohl, Chirag Nagpal, Maria Nagawa, Abigail Oppong, Sanmi Koyejo, Katherine A. Heller

Proceedings of the 4th ACM Conference on Equity and Access in Algorithms, 2024

2023

Benchmarking Continuous Time Models for Predicting Multiple Sclerosis Progression.

Alexander Luke Ian Norcliffe, Lev Proleev, Diana Mincu, Fletcher Lee Hartsell, Katherine A. Heller, Subhrajit Roy

Trans. Mach. Learn. Res., 2023

Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking.

Jacob Eisenstein, Chirag Nagpal, Alekh Agarwal, Ahmad Beirami, Alex D'Amour, Dj Dvijotham, Adam Fisch, Katherine A. Heller, Stephen Pfohl, Deepak Ramachandran, Peter Shaw, Jonathan Berant

CoRR, 2023

STUDY: Socially Aware Temporally Casual Decoder Recommender Systems.

Eltayeb Ahmed, Diana Mincu, Lauren Harrell, Katherine A. Heller, Subhrajit Roy

CoRR, 2023

Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa.

Mercy Nyamewaa Asiedu, Awa Dieng, Abigail Oppong, Maria Nagawa, Sanmi Koyejo, Katherine A. Heller

CoRR, 2023

Longitudinal Modeling of Multiple Sclerosis using Continuous Time Models.

Alexander Norcliffe, Lev Proleev, Diana Mincu, Fletcher Lee Hartsell, Katherine A. Heller, Subhrajit Roy

CoRR, 2023

Participatory Systems for Personalized Prediction.

Hailey James, Chirag Nagpal, Katherine A. Heller, Berk Ustun

CoRR, 2023

Participatory Personalization in Classification.

Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Underspecification Presents Challenges for Credibility in Modern Machine Learning.

Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley

J. Mach. Learn. Res., 2022

Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?

Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour

CoRR, 2022

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings.

Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M. Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Opportunities for Human-centered Evaluation of Machine Translation Systems.

Daniel Liebling, Katherine A. Heller, Samantha Robertson, Wesley Hanwen Deng

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Healthsheet: Development of a Transparency Artifact for Health Datasets.

Negar Rostamzadeh, Diana Mincu, Subhrajit Roy, Andrew Smart, Lauren Wilcox, Mahima Pushkarna, Jessica Schrouff, Razvan Amironesei, Nyalleng Moorosi, Katherine A. Heller

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Evaluation Gaps in Machine Learning Practice.

Ben Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine A. Heller, Vinodkumar Prabhakaran

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Disability prediction in multiple sclerosis using performance outcome measures and demographic data.

Subhrajit Roy, Diana Mincu, Lev Proleev, Negar Rostamzadeh, Chintan Ghate, Natalie Harris, Christina Chen, Jessica Schrouff, Nenad Tomasev, Fletcher Lee Hartsell, Katherine A. Heller

Proceedings of the Conference on Health, Inference, and Learning, 2022

2021

Variational refinement for importance sampling using the forward Kullback-Leibler divergence.

Ghassen Jerfel, Serena Lutong Wang, Clara Wong-Fannjiang, Katherine A. Heller, Yian Ma, Michael I. Jordan

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Deep Cox Mixtures for Survival Regression.

Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine A. Heller

Proceedings of the Machine Learning for Healthcare Conference, 2021

2020

Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors.

Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran

Proceedings of the 37th International Conference on Machine Learning, 2020

Analyzing the role of model uncertainty for electronic health records.

Michael W. Dusenberry, Dustin Tran, Edward Choi, Jonas Kemp, Jeremy Nixon, Ghassen Jerfel, Katherine A. Heller, Andrew M. Dai

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

2019

Federated and Differentially Private Learning for Electronic Health Records.

Stephen R. Pfohl, Andrew M. Dai, Katherine A. Heller

CoRR, 2019

Reconciling meta-learning and continual learning with online mixtures of tasks.

Ghassen Jerfel, Erin Grant, Tom Griffiths, Katherine A. Heller

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

InverseNet: Solving Inverse Problems of Multimedia Data with Splitting Networks.

Qi Wei, Kai Fan, Wenlin Wang, Tianhang Zheng, Amit Chakraborty, Katherine A. Heller, Changyou Chen, Kui Ren

Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

SMOGS: Social Network Metrics of Game Success.

Fan Bu, Sonia Xu, Katherine A. Heller, Alexander Volfovsky

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Online gradient-based mixtures for transfer modulation in meta-learning.

Ghassen Jerfel, Erin Grant, Thomas L. Griffiths, Katherine A. Heller

CoRR, 2018

Learning Root Source with Marked Multivariate Hawkes Processes.

Wei Zhang, Fan Bu, Derek Owens-Oas, Katherine A. Heller, Xiaojin Zhu

CoRR, 2018

2017

InverseNet: Solving Inverse Problems with Splitting Networks.

Kai Fan, Qi Wei, Wenlin Wang, Amit Chakraborty, Katherine A. Heller

CoRR, 2017

Machine Learning for Healthcare Data.

Katherine A. Heller

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

An inner-loop free solution to inverse problems using deep neural networks.

Kai Fan, Qi Wei, Lawrence Carin, Katherine A. Heller

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Predictive Hierarchical Clustering: Learning clusters of CPT codes for improving surgical outcomes.

Elizabeth C. Lorenzi, Stephanie L. Brown, Zhifei Sun, Katherine A. Heller

Proceedings of the Machine Learning for Health Care Conference, 2017

An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection.

Joseph Futoma, Sanjay Hariharan, Katherine A. Heller, Mark P. Sendak, Nathan Brajer, Meredith Clement, Armando Bedoya, Cara O'Brien

Proceedings of the Machine Learning for Health Care Conference, 2017

Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier.

Joseph Futoma, Sanjay Hariharan, Katherine A. Heller

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Content-based Modeling of Reciprocal Relationships using Hawkes and Gaussian Processes.

Xi Tan, Syed A. Z. Naqvi, Yuan (Alan) Qi, Katherine A. Heller, Vinayak A. Rao

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease.

Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data.

Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller

Proceedings of the 1st Machine Learning in Health Care, 2016

Triply Stochastic Variational Inference for Non-linear Beta Process Factor Analysis.

Kai Fan, Yizhe Zhang, Ricardo Henao, Katherine A. Heller

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

A Unifying Variational Inference Framework for Hierarchical Graph-Coupled HMM with an Application to Influenza Infection.

Kai Fan, Chunyuan Li, Katherine A. Heller

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Parallelizing MCMC with Random Partition Trees.

Xiangyu Wang, Fangjian Guo, Katherine A. Heller, David B. Dunson

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Fast Second Order Stochastic Backpropagation for Variational Inference.

Kai Fan, Ziteng Wang, Jeffrey M. Beck, James T. Kwok, Katherine A. Heller

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Hierarchical Graph-Coupled HMMs for Heterogeneous Personalized Health Data.

Kai Fan, Marisa C. Eisenberg, Alison Walsh, Allison Aiello, Katherine A. Heller

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation.

Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Partial Membership and Factor Analysis.

Zoubin Ghahramani, Shakir Mohamed, Katherine A. Heller

Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014

The Bayesian Echo Chamber: Modeling Influence in Conversations.

Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller

CoRR, 2014

2013

Growing a list.

Benjamin Letham, Cynthia Rudin, Katherine A. Heller

Data Min. Knowl. Discov., 2013

2012

Graph-Coupled HMMs for Modeling the Spread of Infection.

Wen Dong, Alex Pentland, Katherine A. Heller

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Modeling Infection with Multi-agent Dynamics.

Wen Dong, Katherine A. Heller, Alex Pentland

Proceedings of the Social Computing, Behavioral - Cultural Modeling and Prediction, 2012

Modelling Reciprocating Relationships with Hawkes Processes.

Charles Blundell, Katherine A. Heller, Jeffrey M. Beck

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models.

Jeffrey M. Beck, Katherine A. Heller, Alexandre Pouget

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning .

Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Bayesian and L1 Approaches to Sparse Unsupervised Learning

Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani

CoRR, 2011

Small sets of interacting proteins suggest functional linkage mechanisms via Bayesian analogical reasoning.

Edoardo M. Airoldi, Katherine A. Heller, Ricardo Bezerra de Andrade e Silva

Bioinform., 2011

Testing a Bayesian Measure of Representativeness Using a Large Image Database.

Joshua T. Abbott, Katherine A. Heller, Zoubin Ghahramani, Thomas L. Griffiths

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

An Alternative Prior Process for Nonparametric Bayesian Clustering.

Hanna M. Wallach, Shane T. Jensen, Lee H. Dicker, Katherine A. Heller

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Bayesian Rose Trees.

Charles Blundell, Yee Whye Teh, Katherine A. Heller

Proceedings of the UAI 2010, 2010

The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling.

Sinead Williamson, Chong Wang, Katherine A. Heller, David M. Blei

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

Tree-Based Inference for Dirichlet Process Mixtures.

Yang Xu, Katherine A. Heller, Zoubin Ghahramani

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Infinite Hierarchical Hidden Markov Models.

Katherine A. Heller, Yee Whye Teh, Dilan Görür

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Ranking Relations using Analogies in Biological and Information Networks

Ricardo Bezerra de Andrade e Silva, Katherine A. Heller, Zoubin Ghahramani, Edoardo M. Airoldi

CoRR, 2009

R/BHC: fast Bayesian hierarchical clustering for microarray data.

Richard S. Savage, Katherine A. Heller, Yang Xu, Zoubin Ghahramani, William M. Truman, Murray Grant, Katherine J. Denby, David L. Wild

BMC Bioinform., 2009

Hierarchical Learning of Dimensional Biases in Human Categorization.

Katherine A. Heller, Adam Sanborn, Nick Chater

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008

Bayesian Exponential Family PCA.

Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Statistical models for partial membership.

Katherine A. Heller, Sinead Williamson, Zoubin Ghahramani

Proceedings of the Machine Learning, 2008

2007

Analogical Reasoning with Relational Bayesian Sets.

Ricardo Bezerra de Andrade e Silva, Katherine A. Heller, Zoubin Ghahramani

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

A Nonparametric Bayesian Approach to Modeling Overlapping Clusters.

Katherine A. Heller, Zoubin Ghahramani

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

2006

A Simple Bayesian Framework for Content-Based Image Retrieval.

Katherine A. Heller, Zoubin Ghahramani

Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006

2005

A comparative evaluation of two algorithms for Windows Registry Anomaly Detection.

Salvatore J. Stolfo, Frank Apap, Eleazar Eskin, Katherine A. Heller, Shlomo Hershkop, Andrew Honig, Krysta M. Svore

J. Comput. Secur., 2005

Bayesian Sets.

Zoubin Ghahramani, Katherine A. Heller

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Bayesian hierarchical clustering.

Katherine A. Heller, Zoubin Ghahramani

Proceedings of the Machine Learning, 2005