Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery. - Constantin F. Aliferis; Ioannis Tsamardinos; Alexander R. Statnikov; Laura E. Brown (METMBS, 2003)

Autominder: an intelligent cognitive orthotic system for people with memory impairment. - Martha E. Pollack; Laura E. Brown; Dirk Colbry; Colleen E. McCarthy; Cheryl Orosz; Bart Peintner; Sailesh Ramakrishnan; Ioannis Tsamardinos (Robotics Auton. Syst., 2003)

A Novel Algorithm for Scalable and Accurate Bayesian Network Learning. - Laura E. Brown; Ioannis Tsamardinos; Constantin F. Aliferis (MedInfo, 2004)

A Comparison of Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms. - Laura E. Brown; Ioannis Tsamardinos; Constantin F. Aliferis (AAAI, 2005)

Generating Realistic Large Bayesian Networks by Tiling. - Ioannis Tsamardinos; Alexander R. Statnikov; Laura E. Brown; Constantin F. Aliferis (FLAIRS, 2006)

The max-min hill-climbing Bayesian network structure learning algorithm. - Ioannis Tsamardinos; Laura E. Brown; Constantin F. Aliferis (Mach. Learn., 2006)

Comparing Decision Support Methodologies for Identifying Asthma Exacerbations. - Judith W. Dexheimer; Laura E. Brown; Jeffrey Leegon; Dominik Aronsky (MedInfo, 2007)

Bounding the False Discovery Rate in Local Bayesian Network Learning. - Ioannis Tsamardinos; Laura E. Brown (AAAI, 2008)

A Strategy for Making Predictions Under Manipulation. - Laura E. Brown; Ioannis Tsamardinos (WCCI Causation and Prediction Challenge, 2008)

Novel Methods for Variable Selection in Non-faithful Domains, Understanding Support Vector Machines, Learning Regions of Bayesian Networks, and Prediction Under Manipulation. - Laura E. Brown (2009)

Model AI Assignments 2012. - Todd W. Neller; Laura E. Brown; John Earnest; Jason Hiebel; Douglas Turnbull (EAAI, 2012)

To feature space and back: Identifying top-weighted features in polynomial Support Vector Machine models. - Laura E. Brown; Ioannis Tsamardinos; Douglas P. Hardin (Intell. Data Anal., 2012)

EAAI-13 Preface. - Laura E. Brown; David Kauchak (AAAI, 2013)

Perceptions and influencers affecting engineering and computer science student persistence. - Kaitlyn J. Bunker; Laura E. Brown; Leonard Bohmann; Gretchen Hein; Nilufer Onder; Raven R. Rebb (FIE, 2013)

Educational Advances in Artificial Intelligence. - Laura E. Brown; David Kauchak (AI Mag., 2013)

Model AI Assignments 2014. - Todd W. Neller; Laura E. Brown; Roger L. West; James E. Heliotis; Sean Strout; Ivona Bezáková; Bikramjit Banerjee; Daniel Lucas Thompson (AAAI, 2014)

Transfer Learning-Based Co-Run Scheduling for Heterogeneous Datacenters. - Wei Kuang; Laura E. Brown; Zhenlin Wang (AAAI, 2015)

Modeling Cross-Architecture Co-Tenancy Performance Interference. - Wei Kuang; Laura E. Brown; Zhenlin Wang (CCGRID, 2015)

Survey of multi-agent systems for microgrid control. - Abhilash Kantamneni; Laura E. Brown; Gordon G. Parker; Wayne W. Weaver (Eng. Appl. Artif. Intell., 2015)

Selective switching mechanism in virtual machines via support vector machines and transfer learning. - Wei Kuang; Laura E. Brown; Zhenlin Wang (Mach. Learn., 2015)

Model AI Assignments 2016. - Todd W. Neller; Laura E. Brown; James B. Marshall; Lisa Torrey; Nate Derbinsky; Andrew A. Ward; Thomas E. Allen; Judy Goldsmith; Nahom Muluneh (AAAI, 2016)

A Survey of Current Practice and Teaching of AI. - Michael Wollowski; Robert Selkowitz; Laura E. Brown; Ashok K. Goel 001; George Luger; Jim Marshall; Andrew Neel; Todd W. Neller; Peter Norvig (AAAI, 2016)

Representation and incorporation of clinical information in outpatient oncology prognosis using Bayesian networks and Naïve Bayes. - Jennifer Winikus; Laura E. Brown (EIT, 2016)

Detection of Weight Data-Entry Errors. - Jing Liu; Laura E. Brown; Judith W. Dexheimer; Stephen Andrew Spooner (AMIA, 2017)

An Ontology for Solar Irradiation Forecast Models. - Abhilash Kantamneni; Laura E. Brown (KEOD, 2018)

Constructing Dynamic Policies for Paging Mode Selection. - Jason Hiebel; Laura E. Brown; Zhenlin Wang (ICPP, 2018)

Lab exercises for a discrete structures course: exploring logic and relational algebra with Alloy. - Laura E. Brown; Adam Feltz; Charles Wallace 001 (ITiCSE, 2018)

Machine Learning for Fine-Grained Hardware Prefetcher Control. - Jason Hiebel; Laura E. Brown; Zhenlin Wang (ICPP, 2019)

Prediction of Hour of Coincident Daily Peak Load. - Jinxiang Liu; Laura E. Brown (ISGT, 2019)

Hierarchical Bayesian Model for Probabilistic Analysis of Electric Vehicle Battery Degradation. - Mehdi Jafari; Laura E. Brown; Lucia Gauchia (CoRR, 2019)

A Few-shot Learning Model based on a Triplet Network for the Prediction of Energy Coincident Peak Days. - Jinxiang Liu; Laura E. Brown (FLAIRS, 2022)

Work-in-Progress: Preliminary Work Introducing Automated Code Critiques in First-Year Engineering MATLAB Programming. - Laura Albrant; Pradnya Pendse; Laura E. Brown; Jon Sticklen; Michelle Jarvie-Eggart; Leo C. Ureel (FIE, 2023)

Work-in-Progress: Python Code Critiquer, a Machine Learning Approach. - Laura Albrant; Pradnya Pendse; Danieal Dasker; Laura E. Brown; Jon Sticklen; Michelle Jarvie-Eggart; Leo C. Ureel (FIE, 2023)

Engaging Novice Programmers: A Literature Review of the Effect of Code Critiquers on Programming Self-efficacy. - Mary E. Benjamin; Laura E. Brown; Jon Sticklen; Leo C. Ureel; Michelle Jarvie-Eggart (FIE, 2023)

Extending the Usability of WebTA with Unified ASTs and Errors. - Joseph Roy Teahen; Daniel T. Masker; Leo C. Ureel; Michelle Jarvie-Eggart; Jon Sticklen; Laura E. Brown (FIE, 2023)