Towards Comparative Physical Interpretation of Spatial Variability Aware Neural Networks: A Summary of Results. - Jayant Gupta; Carl Molnar; Gaoxiang Luo; Joe Knight; Shashi Shekhar 001 (CoRR, 2021)

MC-DGCNN: A Novel DNN Architecture for Multi-Category Point Set Classification. - Majid Farhadloo; Carl Molnar; Gaoxiang Luo; Yan Li 049; Shashi Shekhar 001; Rachel L. Maus; Svetomir N. Markovic; Raymond Moore; Alexey A. Leontovich (CoRR, 2021)

Spatial Variability Aware Deep Neural Networks (SVANN): A General Approach. - Jayant Gupta; Carl Molnar; Yiqun Xie; Joe Knight; Shashi Shekhar 001 (ACM Trans. Intell. Syst. Technol., 2021)

SAMCNet: Towards a Spatially Explainable AI Approach for Classifying MxIF Oncology Data. - Majid Farhadloo; Carl Molnar; Gaoxiang Luo; Yan Li 049; Shashi Shekhar 001; Rachel L. Maus; Svetomir N. Markovic; Alexey A. Leontovich; Raymond Moore (KDD, 2022)

A Survey on Solving and Discovering Differential Equations Using Deep Neural Networks. - Hyeonjung (Tari) Jung; Jayant Gupta; Bharat Jayaprakash; Matthew Eagon; Harish Panneer Selvam; Carl Molnar; William F. Northrop; Shashi Shekhar 001 (CoRR, 2023)

IHCScoreGAN: An unsupervised generative adversarial network for end-to-end ki67 scoring for clinical breast cancer diagnosis. - Carl Molnar; Thomas E. Tavolara; Christopher A. Garcia; David S. McClintock; Mark D. Zarella; Wenchao Han (MIDL, 2024)