引用次数
引用: 40,449
H-指数: 45
I10-指数 : 80
出版物: 234
influences survival in follicular lymphoma patients A pluripotency signature predicts histologic tra
Andrew J. Gentles , Sylvia K. Plevritis , Su-in Lee , Ash A. Alizadeh
2012
Learning graphical models with hubs
Daniela Witten , Maryam Fazel , Kean Ming Tan , Su-In Lee
Journal of Machine Learning Research 15 ( 1) 3297 -3331
61
2014
ChromNet Data Bundle build 3
Brian Raught , Linda Penn , Su-In Lee , William Tu
2016
MYC, HCFC1 PLA validation images from ChromNet paper
Brian Raught , Su-In Lee , William Tu , Scott Lundberg
2016
An unexpected unity among methods for interpreting model predictions
Su-In Lee , Scott Lundberg
arXiv: Artificial Intelligence
54
2016
influences survival in follicular lymphoma patients A pluripotency signature predicts histologic transformation and
Andrew J. Gentles , Sylvia K. Plevritis , Su-In Lee , Ash A. Alizadeh
2013
A Unified Approach to Interpreting Model Predictions
Su-In Lee , Scott Lundberg
arXiv: Artificial Intelligence
668
2017
Consistent feature attribution for tree ensembles
Su-In Lee , Scott M. Lundberg
arXiv: Artificial Intelligence
101
2017
Unsupervised learning of features in multiple gene expression datasets reveals a potential driver for tumor-associated stroma
Mara Rendi , Charles W Drescher , Benjamin A Logsdon , Su-In Lee
F1000Research 5
2016
Checkpoint Ensembles: Ensemble Methods from a Single Training Process
Su-In Lee , Scott Lundberg , Hugh Chen
arXiv: Learning
19
2017
Anesthesiologist-level forecasting of hypoxemia with only SpO2 data using deep learning
Su-In Lee , Scott M. Lundberg , Hugh Chen , Gabriel G. Erion
arXiv: Learning
2
2017
Hybrid Gradient Boosting Trees and Neural Networks for Forecasting Operating Room Data
Su-In Lee , Scott Lundberg , Hugh Chen
arXiv: Learning
2
2018
Consistent Individualized Feature Attribution for Tree Ensembles.
Su-In Lee , Scott M. Lundberg , Gabriel G. Erion
arXiv: Learning
7
2018
A probabilistic approach to using big data reveals Complex I as a potential Alzheimer's disease therapeutic target
Jennifer F. Bobb , C. Dirk Keene , Matt Kaeberlein , Su-In Lee
bioRxiv 302737
1
2018
Node-Based Learning of Multiple Gaussian Graphical Models
Daniela Witten , Maryam Fazel , Su-In Lee , Karthik Mohan
arXiv: Machine Learning
2
2013
Learning Graphical Models With Hubs
Daniela Witten , Maryam Fazel , Kean Ming Tan , Su-In Lee
arXiv: Machine Learning
2
2014
Barriers to Successful Implementation of Precision Medicine to the Treatment of Refractory AML: Lessons Learned
Evandro D Bezerra , Sylvia Chien , Timothy Martins , Cody Hammer
Blood 130 4622 -4622
2017
Explaining Models by Propagating Shapley Values of Local Components
Su-In Lee , Scott Lundberg , Hugh Chen
arXiv: Learning
79
2019
Learned Feature Attribution Priors.
Su-In Lee , Joseph D. Janizek , Ethan Weinberger
arXiv: Learning
2019
Learning Deep Attribution Priors Based On Prior Knowledge.
Su-In Lee , Joseph Janizek , Ethan Weinberger
arXiv: Learning
1
2019