A unified approach to interpreting model predictions S Lundberg, SI Lee
NeurIPS (arXiv preprint arXiv:1705.07874), 2017
31050 2017 From local explanations to global understanding with explainable AI for trees SM Lundberg, G Erion, H Chen, A DeGrave, JM Prutkin, B Nair, R Katz, ...
Nature machine intelligence 2 (1), 56-67, 2020
5645 2020 Consistent individualized feature attribution for tree ensembles SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888, 2018
2447 2018 Explainable machine-learning predictions for the prevention of hypoxaemia during surgery SM Lundberg, B Nair, MS Vavilala, M Horibe, MJ Eisses, T Adams, ...
Nature biomedical engineering 2 (10), 749-760, 2018
1676 2018 Sequencing of Aspergillus nidulans and comparative analysis with A. fumigatus and A. oryzae JE Galagan, SE Calvo, C Cuomo, LJ Ma, JR Wortman, S Batzoglou, ...
Nature 438 (7071), 1105-1115, 2005
1650 2005 Massively parallel functional dissection of mammalian enhancers in vivo RP Patwardhan, JB Hiatt, DM Witten, MJ Kim, RP Smith, D May, C Lee, ...
Nature biotechnology 30 (3), 265-270, 2012
636 2012 AI for radiographic COVID-19 detection selects shortcuts over signal AJ DeGrave, JD Janizek, SI Lee
Nature Machine Intelligence 3 (7), 610-619, 2021
635 2021 Efficient l~ 1 regularized logistic regression SI Lee, H Lee, P Abbeel, AY Ng
Aaai 6, 401-408, 2006
560 2006 Understanding global feature contributions with additive importance measures I Covert, SM Lundberg, SI Lee
Advances in Neural Information Processing Systems 33, 17212-17223, 2020
423 2020 Explainable AI for trees: From local explanations to global understanding SM Lundberg, G Erion, H Chen, A DeGrave, JM Prutkin, B Nair, R Katz, ...
arXiv preprint arXiv:1905.04610, 2019
416 2019 Learning generative models for protein fold families S Balakrishnan, H Kamisetty, JG Carbonell, SI Lee, CJ Langmead
Proteins: Structure, Function, and Bioinformatics 79 (4), 1061-1078, 2011
391 2011 A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia SI Lee, S Celik, BA Logsdon, SM Lundberg, TJ Martins, VG Oehler, ...
Nature communications 9 (1), 42, 2018
381 2018 Application of independent component analysis to microarrays SI Lee, S Batzoglou
Genome biology 4, 1-21, 2003
368 2003 A unified approach to interpreting model predictions. arXiv. 2017. doi: 10.48550 S Lundberg, SI Lee
arXiv preprint arXiv.1705.07874 1705, 0
364 * Explaining by removing: A unified framework for model explanation I Covert, S Lundberg, SI Lee
Journal of Machine Learning Research 22 (209), 1-90, 2021
335 * 2021 Efficient Structure Learning of Markov Networks using SI Lee, V Ganapathi, D Koller
Advances in neural Information processing systems, 2006
313 2006 Explaining a Series of Models by Propagating Shapley Values H Chen, SM Lundberg, SI Lee
Nature Communications, 2021
266 * 2021 Improving performance of deep learning models with axiomatic attribution priors and expected gradients G Erion, JD Janizek, P Sturmfels, SM Lundberg, SI Lee
Nature machine intelligence 3 (7), 620-631, 2021
262 2021 The proteomic landscape of triple-negative breast cancer RT Lawrence, EM Perez, D Hernández, CP Miller, KM Haas, HY Irie, ...
Cell reports 11 (4), 630-644, 2015
258 2015 Visualizing the impact of feature attribution baselines P Sturmfels, S Lundberg, SI Lee
Distill 5 (1), e22, 2020
249 2020 
Scott LundbergGoogle DeepMindПодтвержден адрес электронной почты в домене google.com