Jacob Fein-Ashley

According to our database, Jacob Fein-Ashley authored at least 11 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

The FFT Strikes Back: An Efficient Alternative to Self-Attention.

Jacob Fein-Ashley

CoRR, February, 2025

Linear Diffusion Networks.

Jacob Fein-Ashley

CoRR, February, 2025

Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence.

Jacob Fein-Ashley

CoRR, February, 2025

ClusterViG: Efficient Globally Aware Vision GNNs via Image Partitioning.

Dhruv Parikh, Jacob Fein-Ashley, Tian Ye, Rajgopal Kannan, Viktor K. Prasanna

CoRR, January, 2025

2024

Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback.

Jacob Fein-Ashley

CoRR, 2024

Diffusion Models with Anisotropic Gaussian Splatting for Image Inpainting.

Jacob Fein-Ashley, Benjamin Fein-Ashley

CoRR, 2024

HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean Space.

Jacob Fein-Ashley, Ethan Feng, Minh Pham

CoRR, 2024

Studying the Effects of Self-Attention on SAR Automatic Target Recognition.

Jacob Fein-Ashley, Rajgopal Kannan, Viktor K. Prasanna

CoRR, 2024

A Comparison of Traditional and Deep Learning Methods for Parameter Estimation of the Ornstein-Uhlenbeck Process.

Jacob Fein-Ashley

CoRR, 2024

A Single Graph Convolution is All You Need: Efficient Grayscale Image Classification.

Jacob Fein-Ashley, Sachini Wickramasinghe, Bingyi Zhang, Rajgopal Kannan, Viktor K. Prasanna

Proceedings of the IEEE International Conference on Image Processing, 2024

2023

Benchmarking Deep Learning Classifiers for SAR Automatic Target Recognition.

Jacob Fein-Ashley, Tian Ye, Rajgopal Kannan, Viktor K. Prasanna, Carl E. Busart

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023