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Scott Lundberg
Scott Lundberg
Google DeepMind
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Title
Cited by
Cited by
Year
A unified approach to interpreting model predictions
SM Lundberg, SI Lee
Advances in neural information processing systems 30, 2017
195182017
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
36082020
Consistent individualized feature attribution for tree ensembles
SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888, 2018
16292018
Sparks of artificial general intelligence: Early experiments with gpt-4
S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
arXiv preprint arXiv:2303.12712, 2023
14472023
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
12732018
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
3182019
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
2872018
Understanding global feature contributions with additive importance measures
I Covert, SM Lundberg, SI Lee
Advances in Neural Information Processing Systems 33, 17212-17223, 2020
2432020
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
1932021
Visualizing the impact of feature attribution baselines
P Sturmfels, S Lundberg, SI Lee
Distill 5 (1), e22, 2020
1762020
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
1612021
An unexpected unity among methods for interpreting model predictions
S Lundberg, SI Lee
arXiv preprint arXiv:1611.07478, 2016
1472016
True to the model or true to the data?
H Chen, JD Janizek, S Lundberg, SI Lee
arXiv preprint arXiv:2006.16234, 2020
1432020
Consistent feature attribution for tree ensembles
SM Lundberg, SI Lee
arXiv preprint arXiv:1706.06060, 2017
1392017
A unified approach to interpreting model predictions. arXiv 2017
S Lundberg, SI Lee
arXiv preprint arXiv:1705.07874, 2022
1352022
Sparks of artificial general intelligence: early experiments with GPT-4. arXiv
S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
1152023
Explaining models by propagating Shapley values of local components
H Chen, S Lundberg, SI Lee
Explainable AI in Healthcare and Medicine: Building a Culture of …, 2021
1002021
Shapley flow: A graph-based approach to interpreting model predictions
J Wang, J Wiens, S Lundberg
International Conference on Artificial Intelligence and Statistics, 721-729, 2021
962021
Consistent individualized feature attribution for tree ensembles. arXiv 2018
SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888, 1802
941802
Learning explainable models using attribution priors
G Erion, JD Janizek, P Sturmfels, SM Lundberg, SI Lee
792019
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