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Andy Liaw
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2020 – today
- 2024
- [i3]Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski:
Challenges in Variable Importance Ranking Under Correlation. CoRR abs/2402.03447 (2024) - 2023
- [i2]Yuting Xu, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik:
Development and Evaluation of Conformal Prediction Methods for QSAR. CoRR abs/2304.00970 (2023) - 2021
- [i1]Robert P. Sheridan, Andy Liaw, Matthew Tudor:
Light Gradient Boosting Machine as a Regression Method for Quantitative Structure-Activity Relationships. CoRR abs/2105.08626 (2021) - 2020
- [j11]Robert P. Sheridan
, Min Wang, Andy Liaw, Junshi Ma, Eric M. Gifford:
Correction to Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 60(3): 1910 (2020) - [j10]Robert P. Sheridan
Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models? J. Chem. Inf. Model. 60(4): 1969-1982 (2020) - [j9]Yuting Xu
Deep Dive into Machine Learning Models for Protein Engineering. J. Chem. Inf. Model. 60(6): 2773-2790 (2020) - [j8]Anthony Difranzo
Nearest Neighbor Gaussian Process for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 60(10): 4653-4663 (2020)
2010 – 2019
- 2019
- [j7]Dai Feng
Building Quantitative Structure-Activity Relationship Models Using Bayesian Additive Regression Trees. J. Chem. Inf. Model. 59(6): 2642-2655 (2019) - 2018
- [c2]Huijun Wang, Francisco Garcia, An Chi, Ivan Cornella Taracido, Anne Mai Wasssermann, Andy Liaw:
Profiling Diverse Chemical Space to Map the Druggable Proteome. BCB 2018: 516 - 2017
- [j6]Yuting Xu
Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 57(10): 2490-2504 (2017) - 2016
- [j5]Robert P. Sheridan
Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 56(12): 2353-2360 (2016) - 2015
- [j4]Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik:
Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 55(2): 263-274 (2015)
2000 – 2009
- 2009
- [j3]Junshui Ma, Christopher Tong
Generating hypotheses about molecular structure-activity relationships (SARs) by solving an optimization problem. Stat. Anal. Data Min. 2(3): 161-174 (2009) - 2005
- [j2]Vladimir Svetnik, Ting Wang, Christopher Tong
Boosting: An Ensemble Learning Tool for Compound Classification and QSAR Modeling. J. Chem. Inf. Model. 45(3): 786-799 (2005) - 2004
- [c1]Vladimir Svetnik, Andy Liaw, Christopher Tong, Ting Wang:
Application of Breiman's Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules. Multiple Classifier Systems 2004: 334-343 - 2003
- [j1]Vladimir Svetnik, Andy Liaw, Christopher Tong
Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling. J. Chem. Inf. Comput. Sci. 43(6): 1947-1958 (2003)
Coauthor Index
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