Benchmarking Deep Learning Classifiers for SAR Automatic Target Recognition. - Jacob Fein-Ashley; Tian Ye 002; Rajgopal Kannan; Viktor K. Prasanna; Carl E. Busart (HPEC, 2023)

A Single Graph Convolution is All You Need: Efficient Grayscale Image Classification. - Jacob Fein-Ashley; Sachini Wickramasinghe; Bingyi Zhang; Rajgopal Kannan; Viktor K. Prasanna (ICIP, 2024)

A Comparison of Traditional and Deep Learning Methods for Parameter Estimation of the Ornstein-Uhlenbeck Process. - Jacob Fein-Ashley (CoRR, 2024)

Studying the Effects of Self-Attention on SAR Automatic Target Recognition. - Jacob Fein-Ashley; Rajgopal Kannan; Viktor K. Prasanna (CoRR, 2024)

HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean Space. - Jacob Fein-Ashley; Ethan Feng; Minh Pham (CoRR, 2024)

Diffusion Models with Anisotropic Gaussian Splatting for Image Inpainting. - Jacob Fein-Ashley; Benjamin Fein-Ashley (CoRR, 2024)

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback. - Jacob Fein-Ashley (CoRR, 2024)

ClusterViG: Efficient Globally Aware Vision GNNs via Image Partitioning. - Dhruv Parikh; Jacob Fein-Ashley; Tian Ye 002; Rajgopal Kannan; Viktor K. Prasanna (CoRR, 2025)

Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence. - Jacob Fein-Ashley (CoRR, 2025)

Linear Diffusion Networks. - Jacob Fein-Ashley (CoRR, 2025)

The FFT Strikes Back: An Efficient Alternative to Self-Attention. - Jacob Fein-Ashley (CoRR, 2025)