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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
228352017
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
42422020
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
21672023
Consistent individualized feature attribution for tree ensembles
SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888, 2018
18322018
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
13932018
Advances in neural information processing systems
SM Lundberg, SI Lee, I Guyon, UV Luxburg, S Bengio
Guyon, UV Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R …, 2017
5962017
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
3492019
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
3252018
Understanding global feature contributions with additive importance measures
I Covert, SM Lundberg, SI Lee
Advances in Neural Information Processing Systems 33, 17212-17223, 2020
2852020
Sparks of artificial general intelligence: Early experiments with GPT-4. arXiv
S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
arXiv preprint arXiv:2303.12712, 2023
2252023
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
2182021
Visualizing the impact of feature attribution baselines
P Sturmfels, S Lundberg, SI Lee
Distill 5 (1), e22, 2020
2032020
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
1922021
Consistent feature attribution for tree ensembles
SM Lundberg, SI Lee
arXiv preprint arXiv:1706.06060, 2017
1592017
True to the model or true to the data?
H Chen, JD Janizek, S Lundberg, SI Lee
arXiv preprint arXiv:2006.16234, 2020
1572020
An unexpected unity among methods for interpreting model predictions
S Lundberg, SI Lee
arXiv preprint arXiv:1611.07478, 2016
1562016
Art: Automatic multi-step reasoning and tool-use for large language models
B Paranjape, S Lundberg, S Singh, H Hajishirzi, L Zettlemoyer, ...
arXiv preprint arXiv:2303.09014, 2023
1172023
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
1152021
Consistent individualized feature attribution for tree ensembles. arXiv 2018
SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888 10, 1802
1051802
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
1032021
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Articles 1–20