Scott Lundberg
Scott Lundberg
Verified email at cs.washington.edu - Homepage
TitleCited byYear
A unified approach to interpreting model predictions
SM Lundberg, SI Lee
Advances in Neural Information Processing Systems, 4765-4774, 2017
4232017
Consistent individualized feature attribution for tree ensembles
SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888, 2018
752018
An unexpected unity among methods for interpreting model predictions
S Lundberg, SI Lee
arXiv preprint arXiv:1611.07478, 2016
422016
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
382018
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, 2018
242018
ChromNet: Learning the human chromatin network from all ENCODE ChIP-seq data
SM Lundberg, WB Tu, B Raught, LZ Penn, MM Hoffman, SI Lee
Genome biology 17 (1), 82, 2016
222016
Consistent feature attribution for tree ensembles
SM Lundberg, SI Lee
arXiv preprint arXiv:1706.06060, 2017
102017
Explainable machine learning predictions to help anesthesiologists prevent hypoxemia during surgery
SM Lundberg, B Nair, MS Vavilala, M Horibe, MJ Eisses, T Adams, ...
bioRxiv, 206540, 2017
72017
Lossy compression of data points using point-wise error constraints
RC Paffenroth, R Nong, WD Leed, SM Lundberg
US Patent 8,811,758, 2014
72014
Checkpoint Ensembles: Ensemble Methods from a Single Training Process
H Chen, S Lundberg, SI Lee
arXiv preprint arXiv:1710.03282, 2017
52017
Design Without Borders: A Multi-Everything Masters
J Stevens
Proceedings from 3rd International Conference for Design Education …, 2015
42015
An implicit representation of chordal comparabilty graphs in linear-time
AR Curtis, C Izurieta, B Joeris, S Lundberg, RM McConnell
International Workshop on Graph-Theoretic Concepts in Computer Science, 168-178, 2006
42006
CloudControl: Leveraging many public ChIP-seq control experiments to better remove background noise
N Hiranuma, S Lundberg, SI Lee
Proceedings of the 7th ACM International Conference on Bioinformatics …, 2016
32016
An implicit representation of chordal comparability graphs in linear time
AR Curtis, C Izurieta, B Joeris, S Lundberg, RM McConnell
Discrete Applied Mathematics 158 (8), 869-875, 2010
32010
AIControl: Replacing matched control experiments with machine learning improves ChIP-seq peak identification
N Hiranuma, SM Lundberg, SI Lee
Nucleic acids research 47 (10), e58-e58, 2019
22019
Hybrid Gradient Boosting Trees and Neural Networks for Forecasting Operating Room Data
H Chen, S Lundberg, SI Lee
arXiv preprint arXiv:1801.07384, 2018
22018
DeepATAC: A deep-learning method to predict regulatory factor binding activity from ATAC-seq signals
N Hiranuma, S Lundberg, SI Lee
bioRxiv, 172767, 2017
22017
Analysis of CBRN sensor fusion methods
S Lundberg, R Paffenroth, J Yosinski
2010 13th International Conference on Information Fusion, 1-8, 2010
22010
Algorithms for distributed chemical sensor fusion
S Lundberg, R Paffenroth, J Yosinski
Signal and Data Processing of Small Targets 2010 7698, 769806, 2010
22010
O (mlogn) split decomposition of strongly-connected graphs
BL Joeris, S Lundberg, RM McConnell
Discrete Applied Mathematics 158 (7), 779-799, 2010
22010
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Articles 1–20