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Lee, Su-In

  1. A Unified Approach to Interpreting Model Predictions
    2017/05/22 by Scott Lundberg, Su-In Lee, Lundberg, Scott +2 · 1 voice · 921 citations
    Computer Science · Mathematics · #Bayesian Modeling and Causal Inference #Explainable Artificial Intelligence (XAI) #Machine Learning and Data Classification #cs.AI #cs.LG #stat.ML
  2. Consistent Individualized Feature Attribution for Tree Ensembles
    2018/02/12 by Scott Lundberg, Gabriel Erion, Lundberg, Scott M. +3 · 52 citations
    Environmental Science · Computer Science · #Forest ecology and management #Explainable Artificial Intelligence (XAI) #Data Analysis with R
  3. Explaining by Removing: A Unified Framework for Model Explanation
    2020/11/21 by Ian Covert, Scott Lundberg, Covert, Ian +3 · 27 citations
    Computer Science · Mathematics · #Advanced Causal Inference Techniques #Bayesian Modeling and Causal Inference #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  4. Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression
    2020/12/02 by Ian Covert, Covert, Ian, Su‐In Lee +1 · 13 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #Machine Learning and Data Classification #Bayesian Modeling and Causal Inference
  5. Algorithms to estimate Shapley value feature attributions
    2022/07/15 by Hugh Chen, Chen, Hugh, Ian Covert +5 · 13 citations
    Computer Science · #Bayesian Modeling and Causal Inference #Computer Science and Game Theory (cs.GT) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
  6. True to the Model or True to the Data?
    2020/06/29 by Hugh Chen, Chen, Hugh, Joseph D. Janizek +5 · 13 citations
    Computer Science · Mathematics · #Explainable Artificial Intelligence (XAI) #Bayesian Modeling and Causal Inference #Statistical Methods and Inference
  7. FastSHAP: Real-Time Shapley Value Estimation
    2021/07/15 by Neil Jethani, Mukund Sudarshan, Jethani, Neil +7 · 10 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #Machine Learning in Healthcare #Adversarial Robustness in Machine Learning
  8. Explaining Explanations: Axiomatic Feature Interactions for Deep Networks
    2020/02/10 by Janizek, Joseph D., Sturmfels, Pascal, Lee, Su-In · 6 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  9. Learning to Maximize Mutual Information for Dynamic Feature Selection
    2023/01/02 by Covert, Ian, Qiu, Wei, Lu, Mingyu +3 · 8 citations
    #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  10. Explainable AI for Trees: From Local Explanations to Global Understanding
    2019/05/11 by Scott Lundberg, Lundberg, Scott M., Gabriel Erion +17 · 6 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #Machine Learning in Healthcare
  11. Estimating Conditional Mutual Information for Dynamic Feature Selection
    2023/06/05 by Gadgil, Soham, Covert, Ian, Lee, Su-In · 5 citations
    #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG)
  12. Learning to Estimate Shapley Values with Vision Transformers
    2022/06/10 by Covert, Ian, Kim, Chanwoo, Lee, Su-In · 4 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  13. Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution
    2024/01/29 by Ian Covert, Covert, Ian, Chanwoo Kim +8 · 2 voices · 3 citations
    Computer Science · #Machine Learning and Data Classification
  14. Checkpoint Ensembles: Ensemble Methods from a Single Training Process
    2017/10/09 by Chen, Hugh, Lundberg, Scott, Lee, Su-In · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  15. Explaining Models by Propagating Shapley Values of Local Components
    2019/11/27 by Chen, Hugh, Lundberg, Scott, Lee, Su-In · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  16. Moment Matching Deep Contrastive Latent Variable Models
    2022/02/21 by Weinberger, Ethan, Beebe-Wang, Nicasia, Lee, Su-In · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  17. Node-Based Learning of Multiple Gaussian Graphical Models
    2013/03/21 by Mohan, Karthik, London, Palma, Fazel, Maryam +2 · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  18. Learning Graphical Models With Hubs
    2014/02/28 by Tan, Kean Ming, London, Palma, Mohan, Karthik +3 · 1 citation
    #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
  19. On the Robustness of Removal-Based Feature Attributions
    2023/06/12 by Lin, Chris, Covert, Ian, Lee, Su-In · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  20. Consistent feature attribution for tree ensembles
    2017/06/19 by Lundberg, Scott M., Lee, Su-In · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  21. Hybrid Gradient Boosting Trees and Neural Networks for Forecasting Operating Room Data
    2018/01/23 by Hugh Chen, Scott Lundberg, Chen, Hugh +3 · 1 citation
    Computer Science · Health Professions · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Healthcare #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare #Time Series Analysis and Forecasting
  22. Feature Selection in the Contrastive Analysis Setting
    2023/10/27 by Weinberger, Ethan, Covert, Ian, Lee, Su-In · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  23. Improving performance of deep learning models with axiomatic attribution priors and expected gradients
    2019/06/25 by Erion, Gabriel, Janizek, Joseph D., Sturmfels, Pascal +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  24. An Adversarial Approach for the Robust Classification of Pneumonia from Chest Radiographs
    2020/01/13 by Janizek, Joseph D., Erion, Gabriel, DeGrave, Alex J. +1 · 1 citation
    #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #electronic engineering #information engineering
  25. An Efficient Framework for Crediting Data Contributors of Diffusion Models
    2024/06/09 by Lin, Chris, Lu, Mingyu, Kim, Chanwoo +1 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  26. Explainable AI for computational pathology identifies model limitations and tissue biomarkers
    2024/09/04 by Jakub R. Kaczmarzyk, Jakub Kaczmarzyk, Kim, Chanwoo +14 · 1 voice · 1 citation
    Computer Science · Medicine · #Explainable Artificial Intelligence (XAI) #AI in cancer detection #Artificial Intelligence in Healthcare and Education