| Do no harm: a roadmap for responsible machine learning for health care J Wiens, S Saria, M Sendak, M Ghassemi, VX Liu, F Doshi-Velez, K Jung, ... Nature medicine 25 (9), 1337-1340, 2019 | 1125 | 2019 |
| Underspecification presents challenges for credibility in modern machine learning A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ... Journal of Machine Learning Research 23 (226), 1-61, 2022 | 1027 | 2022 |
| Bayesian hierarchical clustering KA Heller, Z Ghahramani Proceedings of the 22nd international conference on Machine learning, 297-304, 2005 | 525 | 2005 |
| Efficient and scalable bayesian neural nets with rank-1 factors M Dusenberry, G Jerfel, Y Wen, Y Ma, J Snoek, K Heller, ... International conference on machine learning, 2782-2792, 2020 | 298 | 2020 |
| The value of standards for health datasets in artificial intelligence-based applications A Arora, JE Alderman, J Palmer, S Ganapathi, E Laws, MD Mccradden, ... Nature medicine 29 (11), 2929-2938, 2023 | 292 | 2023 |
| One class support vector machines for detecting anomalous windows registry accesses K Heller, K Svore, AD Keromytis, S Stolfo | 278 | 2003 |
| Modelling reciprocating relationships with Hawkes processes C Blundell, J Beck, KA Heller Advances in neural information processing systems 25, 2012 | 263 | 2012 |
| A shared vision for machine learning in neuroscience MAT Vu, T Adalı, D Ba, G Buzsáki, D Carlson, K Heller, C Liston, C Rudin, ... Journal of Neuroscience 38 (7), 1601-1607, 2018 | 255 | 2018 |
| Learning to detect sepsis with a multitask Gaussian process RNN classifier J Futoma, S Hariharan, K Heller International conference on machine learning, 1174-1182, 2017 | 255 | 2017 |
| Real-world integration of a sepsis deep learning technology into routine clinical care: implementation study MP Sendak, W Ratliff, D Sarro, E Alderton, J Futoma, M Gao, M Nichols, ... JMIR medical informatics 8 (7), e15182, 2020 | 224 | 2020 |
| Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): a … KM Corey, S Kashyap, E Lorenzi, SA Lagoo-Deenadayalan, K Heller, ... PLoS medicine 15 (11), e1002701, 2018 | 223 | 2018 |
| The IBP compound Dirichlet process and its application to focused topic modeling S Williamson, C Wang, KA Heller, DM Blei Proceedings of the 27th international conference on machine learning (ICML …, 2010 | 217 | 2010 |
| Bayesian sets Z Ghahramani, KA Heller Advances in neural information processing systems 18, 2005 | 196 | 2005 |
| An improved multi-output gaussian process rnn with real-time validation for early sepsis detection J Futoma, S Hariharan, K Heller, M Sendak, N Brajer, M Clement, ... Machine learning for healthcare conference, 243-254, 2017 | 192 | 2017 |
| An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands J Jiang, J Beck, K Heller, T Egner Nature Communications 6 (1), 8165, 2015 | 187 | 2015 |
| Sequence information for the splicing of human pre-mRNA identified by support vector machine classification XHF Zhang, KA Heller, I Hefter, CS Leslie, LA Chasin Genome Research 13 (12), 2637-2650, 2003 | 182 | 2003 |
| Reconciling meta-learning and continual learning with online mixtures of tasks G Jerfel, E Grant, T Griffiths, KA Heller Advances in neural information processing systems 32, 2019 | 155 | 2019 |
| Bayesian exponential family PCA S Mohamed, Z Ghahramani, KA Heller Advances in neural information processing systems 21, 2008 | 134 | 2008 |
| Analyzing the role of model uncertainty for electronic health records MW Dusenberry, D Tran, E Choi, J Kemp, J Nixon, G Jerfel, K Heller, ... Proceedings of the ACM Conference on Health, Inference, and Learning, 204-213, 2020 | 131 | 2020 |
| Bayesian modeling of flexible cognitive control J Jiang, K Heller, T Egner Neuroscience & Biobehavioral Reviews 46, 30-43, 2014 | 131 | 2014 |
