2 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Diffusion Models with Anisotropic Gaussian Splatting for Image Inpainting
Jacob Fein-Ashley, Benjamin Fein-Ashley
Image inpainting is a fundamental task in computer vision, aiming to restore missing or corrupted regions in images realistically. While recent deep learning approaches have signif…
Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback
Jacob Fein-Ashley, Rajgopal Kannan, Viktor Prasanna
Conventional deep networks rely on one-way backpropagation that overlooks reconciling high-level predictions with lower-level representations. We propose \emph{Contextual Feedback…
HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean Space
Jacob Fein-Ashley, Ethan Feng, Minh Pham
Data representation in non-Euclidean spaces has proven effective for capturing hierarchical and complex relationships in real-world datasets. Hyperbolic spaces, in particular, prov…
A Comparison of Traditional and Deep Learning Methods for Parameter Estimation of the Ornstein-Uhlenbeck Process
Jacob Fein-Ashley
We consider the Ornstein-Uhlenbeck (OU) process, a stochastic process widely used in finance, physics, and biology. Parameter estimation of the OU process is a challenging problem.…