2 citations · 2 across the 5 of their papers we have counts for
5 papers
DINO-MX: A Modular & Flexible Framework for Self-Supervised Learning
Mahmut Selman Gokmen, Cody Bumgardner
Vision Foundation Models (VFMs) have advanced representation learning through self-supervised methods. However, existing training pipelines are often inflexible, domain-specific, o…
Poisson Flow Consistency Training
Anthony Zhang, Mahmut Gokmen, Dennis Hein +4
The Poisson Flow Consistency Model (PFCM) is a consistency-style model based on the robust Poisson Flow Generative Model++ (PFGM++) which has achieved success in unconditional imag…
Enhancing Low Dose Computed Tomography Images Using Consistency Training Techniques
Mahmut S. Gokmen, Jie Zhang, Ge Wang +2
Diffusion models have significant impact on wide range of generative tasks, especially on image inpainting and restoration. Although the improvements on aiming for decreasing numbe…
DINO-LG: Enhancing Vision Transformers with Label Guidance for Coronary Artery Calcium Detection
Mahmut S. Gokmen, Caner Ozcan, Moneera N. Haque +4
Coronary artery disease (CAD), one of the leading causes of mortality worldwide, necessitates effective risk assessment strategies, with coronary artery calcium (CAC) scoring via c…
High Noise Scheduling is a Must
Mahmut S. Gokmen, Cody Bumgardner, Jie Zhang +2
Consistency models possess high capabilities for image generation, advancing sampling steps to a single step through their advanced techniques. Current advancements move one step f…