Su-In Lee
Su-In Lee
Computer Science & Engineering, University of Washington
Verified email at - Homepage
Cited by
Cited by
A unified approach to interpreting model predictions
SM Lundberg, SI Lee
Advances in neural information processing systems 30, 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
Consistent individualized feature attribution for tree ensembles
SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888, 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
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
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
AI for radiographic COVID-19 detection selects shortcuts over signal
AJ DeGrave, JD Janizek, SI Lee
Nature Machine Intelligence 3 (7), 610-619, 2021
Efficient l~ 1 regularized logistic regression
SI Lee, H Lee, P Abbeel, AY Ng
Aaai 6, 401-408, 2006
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
Application of independent component analysis to microarrays
SI Lee, S Batzoglou
Genome biology 4, 1-21, 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
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
Understanding global feature contributions with additive importance measures
I Covert, SM Lundberg, SI Lee
Advances in Neural Information Processing Systems 33, 17212-17223, 2020
Efficient Structure Learning of Markov Networks using -Regularization
SI Lee, V Ganapathi, D Koller
Advances in neural Information processing systems, 2006
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
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
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
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
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
Visualizing the impact of feature attribution baselines
P Sturmfels, S Lundberg, SI Lee
Distill 5 (1), e22, 2020
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