| 2025 | ICAART | Model Characterization with Inductive Orientation Vectors. | Kerria Pang-Naylor, Eric Chen, George D. Montaez |
| 2025 | ICAART | Analyzing and Comparing Machine Learning Models via Inductive Orientation. | Kerria Pang-Naylor, Eric Chen, George D. Montaez |
| 2024 | ICAART | From Targets to Rewards: Continuous Target Sets in the Algorithmic Search Framework. | Milo Knell, Sahil Rane, Forrest Bicker, Tiger Che, Alan Wu, George D. Montaez |
| 2023 | DSAA | Finite-Sample Bounds for Two-Distribution Hypothesis Tests. | Cynthia Hom, William Yik, George D. Montaez |
| 2022 | AIES | Identifying Bias in Data Using Two-Distribution Hypothesis Tests. | William Yik, Limnanthes Serafini, Timothy Lindsey, George D. Montaez |
| 2022 | ICAART | Vectorization of Bias in Machine Learning Algorithms. | Sophie Bekerman, Eric Chen, Lily Lin, George D. Montaez |
| 2022 | ICAART | The Gopher Grounds: Testing the Link between Structure and Function in Simple Machines. | Anshul Kamath, Jiayi Zhao, Nick Grisanti, George D. Montaez |
| 2022 | ICAART | Generating the Gopher's Grounds: Form, Function, Order, and Alignment. | Jiayi Zhao, Anshul Kamath, Nick Grisanti, George D. Montaez |
| 2022 | IJCNN | Bounding Generalization Error Through Bias and Capacity. | Ramya Ramalingam, Nicolas A. Espinosa Dice, Megan L. Kaye, George D. Montaez |
| 2021 | CEC | The Predator's Purpose: Intention Perception in Simulated Agent Environments. | Amani R. Maina-Kilaas, Cynthia Hom, Kevin Ginta, George D. Montaez |
| 2021 | ICAART | A Probabilistic Theory of Abductive Reasoning. | Nicolas A. Espinosa Dice, Megan L. Kaye, Hana Ahmed, George D. Montaez |
| 2021 | ICAART | The Gopher's Gambit: Survival Advantages of Artifact-based Intention Perception. | Cynthia Hom, Amani R. Maina-Kilaas, Kevin Ginta, Cindy Lay, George D. Montaez |
| 2021 | SMC | Hyperparameter Choice as Search Bias in AlphaZero. | Eric M. Weiner, George D. Montaez, Aaron Trujillo, Abtin Molavi |
| 2020 | ICAART | The Bias-Expressivity Trade-off. | Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti, George D. Montaez |
| 2020 | ICAART | Trading Bias for Expressivity in Artificial Learning. | George D. Montaez, Daniel Bashir, Julius Lauw |
| 2020 | ICAART | Decomposable Probability-of-Success Metrics in Algorithmic Search. | Tyler Sam, Jake Williams, Abel Tadesse, Huey Sun, George D. Montaez |
| 2020 | ICAART | The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity. | Pedro Sandoval Segura, Julius Lauw, Daniel Bashir, Kinjal Shah, Sonia Sehra, Dominique Macias, George D. Montaez |
| 2017 | IJCNN | The LICORS cabinet: Nonparametric light cone methods for spatio-temporal modeling. | George D. Montaez, Cosma Rohilla Shalizi |
| 2017 | IRI | Estimating the Prevalence of Religious Content in Intelligent Design Social Media. | George D. Montaez |
| 2017 | SMC | The famine of forte: Few search problems greatly favor your algorithm. | George D. Montaez |
| 2016 | ICAART | Detecting Intelligence - The Turing Test and Other Design Detection Methodologies. | George D. Montaez |
| 2015 | AAAI | Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series. | George D. Montaez, Saeed Amizadeh, Nikolay Laptev |
| 2014 | CIKM | Cross-Device Search. | George D. Montaez, Ryen W. White, Xiao Huang |
| 2013 | CEC | Information transmission through genetic algorithm fitness maps. | George D. Montaez |
| 2013 | CEC | Bounding the number of favorable functions in stochastic search. | George D. Montaez |
| 2012 | CIBCB | Assessing reliability of protein-protein interactions by gene ontology integration. | George D. Montaez, Young-Rae Cho |