Andy Liaw

According to our database1, Andy Liaw authored at least 16 papers between 2003 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Challenges in Variable Importance Ranking Under Correlation.
CoRR, 2024

2023
Development and Evaluation of Conformal Prediction Methods for QSAR.
CoRR, 2023

2021
Light Gradient Boosting Machine as a Regression Method for Quantitative Structure-Activity Relationships.
CoRR, 2021

2020
Deep Dive into Machine Learning Models for Protein Engineering.
J. Chem. Inf. Model., 2020

Correction to Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships.
J. Chem. Inf. Model., 2020

Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models?
J. Chem. Inf. Model., 2020

Nearest Neighbor Gaussian Process for Quantitative Structure-Activity Relationships.
J. Chem. Inf. Model., 2020

2019
Building Quantitative Structure-Activity Relationship Models Using Bayesian Additive Regression Trees.
J. Chem. Inf. Model., 2019

2018
Profiling Diverse Chemical Space to Map the Druggable Proteome.
Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

2017
Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.
J. Chem. Inf. Model., October, 2017

2016
Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships.
J. Chem. Inf. Model., 2016

2015
Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships.
J. Chem. Inf. Model., 2015

2009
Generating hypotheses about molecular structure-activity relationships (SARs) by solving an optimization problem.
Stat. Anal. Data Min., 2009

2005
Boosting: An Ensemble Learning Tool for Compound Classification and QSAR Modeling.
J. Chem. Inf. Model., 2005

2004
Application of Breiman's Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules.
Proceedings of the Multiple Classifier Systems, 5th International Workshop, 2004

2003
Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling.
J. Chem. Inf. Comput. Sci., 2003


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