A unified approach to interpreting model predictions SM Lundberg, SI Lee
Advances in neural information processing systems 30, 2017
17369 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
3224 2020 Consistent individualized feature attribution for tree ensembles SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888, 2018
1603 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
1571 2005 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
1179 2018 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
577 2012 Efficient l~ 1 regularized logistic regression SI Lee, H Lee, P Abbeel, AY Ng
Aaai 6, 401-408, 2006
528 2006 AI for radiographic COVID-19 detection selects shortcuts over signal AJ DeGrave, JD Janizek, SI Lee
Nature Machine Intelligence 3 (7), 610-619, 2021
435 2021 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
363 2011 Application of independent component analysis to microarrays SI Lee, S Batzoglou
Genome biology 4, 1-21, 2003
358 2003 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
307 2019 Efficient Structure Learning of Markov Networks using SI Lee, V Ganapathi, D Koller
Advances in neural Information processing systems, 2006
302 2006 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
265 2018 Understanding global feature contributions with additive importance measures I Covert, SM Lundberg, SI Lee
Advances in Neural Information Processing Systems 33, 17212-17223, 2020
236 * 2020 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
234 2015 Learning a meta-level prior for feature relevance from multiple related tasks SI Lee, V Chatalbashev, D Vickrey, D Koller
Proceedings of the 24th international conference on Machine learning, 489-496, 2007
226 2007 Learning a prior on regulatory potential from eQTL data SI Lee, AM Dudley, D Drubin, PA Silver, NJ Krogan, D Pe'er, D Koller
PLoS genetics 5 (1), e1000358, 2009
221 2009 Node-based learning of multiple Gaussian graphical models K Mohan, P London, M Fazel, D Witten, SI Lee
The Journal of Machine Learning Research 15 (1), 445-488, 2014
213 2014 Explaining by removing: A unified framework for model explanation IC Covert, S Lundberg, SI Lee
The Journal of Machine Learning Research 22 (1), 9477-9566, 2021
198 * 2021 Visualizing the impact of feature attribution baselines P Sturmfels, S Lundberg, SI Lee
Distill 5 (1), e22, 2020
166 2020 
Scott LundbergGoogle DeepMindGeverifieerd e-mailadres voor google.com
