On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval. - Zachary Wilkerson; David Leake; David J. Crandall (ICCBR, 2021)

Extracting Case Indices from Convolutional Neural Networks: A Comparative Study. - David Leake; Zachary Wilkerson; David Crandall (ICCBR, 2022)

DL-CBR Hybridization for Feature Generation and Similarity Assessment. - Zachary Wilkerson (ICCBR Doctoral Consortium, 2022)

Leveraging SHAP and CBR for Dimensionaltiy Reduction on the Psychology Prediction Dataset. - Zachary Wilkerson; David Leake; David Crandall (ICCBR Workshops, 2022)

Examining the Impact of Network Architecture on Extracted Feature Quality for CBR. - David Leake; Zachary Wilkerson; Vibhas Vats; Karan Acharya; David J. Crandall (ICCBR, 2023)

Exploring Deep Learning-Based Feature Extraction for Case-Based Reasoning Retrieval. - Zachary Wilkerson (ICCBR Workshops, 2023)

Enhancing Case-Based Reasoning with Neural Networks. - David Leake; Zachary Wilkerson; Xiaomeng Ye; David J. Crandall (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach. - Zachary Wilkerson; David Leake; Vibhas Vats; David Crandall (ICCBR, 2024)

Learning Case Features with Proxy-Guided Deep Neural Networks. - Vibhas Vats; Zachary Wilkerson; Hiroki Sato; David Leake; David Crandall (ICCBR, 2025)

Extracting Features with Deep Learning for Ensemble-Driven Case-Based Classification. - Zachary Wilkerson; David Leake; David Crandall; Benjamin Wilkerson (ICCBR, 2025)