| 2025 | AAAI | Adaptive Sampling to Reduce Epistemic Uncertainty Using Prediction Interval-Generation Neural Networks. | Giorgio Morales, John W. Sheppard |
| 2025 | FlAIRS | Biasing Exploration towards Positive Error for Efficient Reinforcement Learning. | Adam Parker, John W. Sheppard |
| 2025 | GECCO | Using Variable Interaction Graphs to Improve Particle Swarm Optimization. | Casimir Czworkowski, John W. Sheppard |
| 2025 | IJCNN | Retaining Disadvantaged Students Using a BERT-based Recommender System. | Muhammad Ashfakur Arju, John W. Sheppard, Md Asaduzzaman Noor, Carina Beck, Durward Sobek |
| 2024 | ICMLA | On the Performance and Robustness of Linear Model U-Trees in Mimic Learning. | Matthew Green, John W. Sheppard |
| 2024 | ICMLA | Identifying Hierarchical Community Structures in Content-Based Scholarly Social Networks. | Md Asaduzzaman Noor, John W. Sheppard, Jason A. Clark |
| 2024 | IJCNN | Counterfactual Analysis of Neural Networks Used to Create Fertilizer Management Zones. | Giorgio Morales, John W. Sheppard |
| 2024 | SIGIR | ScholarNodes: Applying Content-based Filtering to Recommend Interdisciplinary Communities within Scholarly Social Networks. | Md Asaduzzaman Noor, Jason A. Clark, John W. Sheppard |
| 2023 | CEC | Evolving Intertask Mappings for Transfer in Reinforcement Learning. | Minh Hua, John W. Sheppard |
| 2023 | GECCO | Factored Particle Swarm Optimization for Policy Co-training in Reinforcement Learning. | Kordel K. France, John W. Sheppard |
| 2023 | IJCNN | Cross-Domain Similarity in Domain Adaptation for Human Activity Recognition. | Samra Kasim, John W. Sheppard |
| 2023 | IJCNN | Counterfactual Explanations of Neural Network-Generated Response Curves. | Giorgio Morales, John W. Sheppard |
| 2021 | CEC | Tournament Topology Particle Swarm Optimization. | Jason Kuo, John W. Sheppard |
| 2021 | EUROGP | Quality Diversity Genetic Programming for Learning Decision Tree Ensembles. | Stephen Boisvert, John W. Sheppard |
| 2020 | IJCNN | Enhancing Neural Networks with Locality-Sensitive Clustering of Internal Representations. | Richard A. McAllister, John W. Sheppard |
| 2020 | IJCNN | Quantifying Uncertainty in Neural Network Ensembles using U-Statistics. | Jordan Schupbach, John W. Sheppard, Tyler Forrester |
| 2020 | IJCNN | Evaluating Explanations of Convolutional Neural Network Image Classifications. | Sumeet S. Shah, John W. Sheppard |
| 2019 | GECCO | Using a genetic algorithm with histogram-based feature selection in hyperspectral image classification. | Neil S. Walton, John W. Sheppard, Joseph A. Shaw |
| 2019 | IJCNN | Efficient Convolutional Neural Networks for Multi-Spectral Image Classification. | Jacob J. Senecal, John W. Sheppard, Joseph A. Shaw |
| 2019 | IJCNN | Using Winning Lottery Tickets in Transfer Learning for Convolutional Neural Networks. | Ryan Van Soelen, John W. Sheppard |
| 2018 | CEC | Pareto Improving Selection of the Global Best in Particle Swarm Optimization. | Stephyn G. W. Butcher, John W. Sheppard, Shane Strasser |
| 2018 | GECCO | An actor model implementation of distributed factored evolutionary algorithms. | Stephyn G. W. Butcher, John W. Sheppard |
| 2018 | GECCO | Comparative performance and scaling of the pareto improving particle swarm optimization algorithm. | Stephyn G. W. Butcher, John W. Sheppard, Brian K. Haberman |
| 2018 | GECCO | Information sharing and conflict resolution in distributed factored evolutionary algorithms. | Stephyn G. W. Butcher, John W. Sheppard, Shane Strasser |
| 2017 | FOGA | Convergence of Factored Evolutionary Algorithms. | Shane Strasser, John W. Sheppard |
| 2016 | CEC | Dynamic sampling in training artificial neural networks with overlapping swarm intelligence. | Shehzad Qureshi, John W. Sheppard |
| 2016 | FlAIRS | A Noisy-OR Model for Continuous Time Bayesian Networks. | Logan Perreault, Shane Strasser, Monica Thornton, John W. Sheppard |
| 2016 | GECCO | Relaxing Consensus in Distributed Factored Evolutionary Algorithms. | Stephyn Butcher, Shane Strasser, Jenna Hoole, Benjamin Demeo, John W. Sheppard |
| 2016 | GECCO | A New Discrete Particle Swarm Optimization Algorithm. | Shane Strasser, Rollie Goodman, John W. Sheppard, Stephyn Butcher |
| 2016 | IJCNN | Assessing diffusion of spatial features in Deep Belief Networks. | Hasari Tosun, Ben Mitchell, John W. Sheppard |
| 2016 | IJCNN | Fast classifier learning under bounded computational resources using Partitioned Restricted Boltzmann Machines. | Hasari Tosun, John W. Sheppard |
| 2015 | GECCO | Parameter Estimation in Bayesian Networks Using Overlapping Swarm Intelligence. | Nathan Fortier, John W. Sheppard, Shane Strasser |
| 2015 | ICDM | Cross-Dataset Validation of Feature Sets in Musical Instrument Classification. | Patrick J. Donnelly, John W. Sheppard |
| 2015 | IJCNN | Deep learning using partitioned data vectors. | Ben Mitchell, Hasari Tosun, John W. Sheppard |
| 2015 | UAI | The Long-Run Behavior of Continuous Time Bayesian Networks. | Liessman Sturlaugson, John W. Sheppard |
| 2014 | FlAIRS | Clustering Spectral Filters for Extensible Feature Extraction in Musical Instrument Classification. | Patrick J. Donnelly, John W. Sheppard |
| 2014 | FlAIRS | Factored Performance Functions with Structural Representation in Continuous Time Bayesian Networks. | Liessman Sturlaugson, John W. Sheppard |
| 2014 | UAI | Inference Complexity in Continuous Time Bayesian Networks. | Liessman Sturlaugson, John W. Sheppard |
| 2013 | FlAIRS | Comparing Frequency- and Style-Based Features for Twitter Author Identification. | Rachel M. Green, John W. Sheppard |
| 2013 | FlAIRS | Cluster Analysis for Optimal Indexing. | Tim Wylie, Michael A. Schuh, John W. Sheppard, Rafal A. Angryk |
| 2012 | FlAIRS | Automated Weather Sensor Quality Control. | Douglas E. Galarus, Rafal A. Angryk, John W. Sheppard |
| 2012 | FlAIRS | Evolving Kernel Functions with Particle Swarms and Genetic Programming. | Michael A. Schuh, Rafal A. Angryk, John W. Sheppard |
| 2012 | ICMLA | Deep Structure Learning: Beyond Connectionist Approaches. | Ben Mitchell, John W. Sheppard |
| 2011 | PERCOM | Incorporating evidence into trust propagation models using Markov Random Fields. | Hasari Tosun, John W. Sheppard |
| 2004 | GECCO | The Royal Road Not Taken: A Re-examination of the Reasons for GA Failure on R1. | Brian Howard, John W. Sheppard |
| 2004 | GECCO | Multi-agent Simulation of Airline Travel Markets. | Rashad L. Moore, Ashley Williams, John W. Sheppard |
| 1998 | SMC | Standard representations of diagnostic models. | William R. Simpson, John W. Sheppard |
| 1997 | ITC | Artificial Intelligence Exchange and Service Tie to All Test Environments (AI-ESTATE)-A New Standard for System Diagnostics. | John W. Sheppard, Leslie A. Orlidge |
| 1996 | VTS | Hardware-Software Co-Design for Test: It's the Last Straw! | J. El-Ziq, Najmi T. Jarwala, Niraj K. Jha, Peter Marwedel, Christos A. Papachristou, Janusz Rajski, John W. Sheppard |
| 1996 | VTS | Improving the accuracy of diagnostics provided by fault dictionaries. | John W. Sheppard, William R. Simpson |
| 1993 | ITC | Testing Fully Testable Systems: A Case Study. | John W. Sheppard |
| 1993 | ITC | The Impact of Commercial Off-The-Shelf (COTS) Equipment on System Test and Diagnosis. | William R. Simpson, John W. Sheppard |
| 1992 | ITC | System Perspective on Diagnostic Testing. | William R. Simpson, John W. Sheppard |
| 1991 | ITC | An Intelligent Approach to Automatic Test Equipment. | William R. Simpson, John W. Sheppard |