Lundberg, Scott M.

A Unified Approach to Interpreting Model Predictions

Lundberg, S., & Lee, S.-I. (2017) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 23,707

From local explanations to global understanding with explainable AI for trees

Lundberg, S. M., Erion, G., Chen, H., DeGrave, A., Prutkin, J. M., Nair, B., Katz, R., Himmelfarb, J., Bansal, N., & Lee, S.-I. (2020) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare

Cited by 10,551

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery

Lundberg, S. M., Nair, B., Vavilala, M. S., Horibe, M., Eisses, M. J., Adams, T., Liston, D. E., Low, D. K.-W., Newman, S.-F., Kim, J., et al. (2018) · Nature Biomedical Engineering

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 1,967

Sparks of Artificial General Intelligence: Early experiments with GPT-4

Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y. T., Li, Y., Lundberg, S., et al. (2023) · arXiv

Topic ModelingArtificial Intelligence Applications

Cited by 1,526

Consistent Individualized Feature Attribution for Tree Ensembles

Lundberg, S. M., Erion, G. G., & Lee, S.-I. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Data Mining Algorithms and Applications

Cited by 1,430

Improving performance of deep learning models with axiomatic attribution priors and expected gradients

Erion, G., Janizek, J. D., Sturmfels, P., Lundberg, S. M., & Lee, S.-I. (2021) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 300

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

Explainable machine learning predictions to help anesthesiologists prevent hypoxemia during surgery

Lundberg, S. M., Nair, B., Vavilala, M. S., Horibe, M., Eisses, M. J., Adams, T., Liston, D. E., Low, D. K.-W., Newman, S.-F., Kim, J., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory)

Machine Learning in HealthcareExplainable Artificial Intelligence (XAI)

Cited by 34