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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
S Lundberg
arXiv preprint arXiv:1705.07874, 2017
288052017
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
52512020
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
32492023
Consistent individualized feature attribution for tree ensembles
SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888, 2018
21512018
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
16112018
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
3972019
Understanding global feature contributions with additive importance measures
I Covert, SM Lundberg, SI Lee
Advances in Neural Information Processing Systems 33, 17212-17223, 2020
3712020
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
3702018
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
3652023
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
2832021
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
2432021
Visualizing the impact of feature attribution baselines
P Sturmfels, S Lundberg, SI Lee
Distill 5 (1), e22, 2020
2392020
Consistent feature attribution for tree ensembles
SM Lundberg, SI Lee
arXiv preprint arXiv:1706.06060, 2017
1872017
True to the model or true to the data?
H Chen, JD Janizek, S Lundberg, SI Lee
arXiv preprint arXiv:2006.16234, 2020
1842020
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
1812023
Algorithms to estimate Shapley value feature attributions
H Chen, IC Covert, SM Lundberg, SI Lee
Nature Machine Intelligence 5 (6), 590-601, 2023
1692023
An unexpected unity among methods for interpreting model predictions
S Lundberg, SI Lee
arXiv preprint arXiv:1611.07478, 2016
1662016
A unified approach to interpreting model predictions. NIPS’17: Proceedings of the 31st International Conference on Neural Information Processing Systems. December 2017 [Cited …
SM Lundberg, SI Lee
165
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
1382021
Consistent individualized feature attribution for tree ensembles. arXiv 2018
SM Lundberg, GG Erion, SI Lee
arXiv preprint arXiv:1802.03888 10, 1802
1331802
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