1 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
Image Generation Diversity Issues and How to Tame Them
Mischa Dombrowski, Weitong Zhang, Sarah Cechnicka +2
Generative methods now produce outputs nearly indistinguishable from real data but often fail to fully capture the data distribution. Unlike quality issues, diversity limitations i…
Truth or Deceit? A Bayesian Decoding Game Enhances Consistency and Reliability
Weitong Zhang, Chengqi Zang, Bernhard Kainz
Large Language Models (LLMs) often produce outputs that -- though plausible -- can lack consistency and reliability, particularly in ambiguous or complex scenarios. Challenges aris…
Universal Topology Refinement for Medical Image Segmentation with Polynomial Feature Synthesis
Liu Li, Hanchun Wang, Matthew Baugh +5
Although existing medical image segmentation methods provide impressive pixel-wise accuracy, they often neglect topological correctness, making their segmentations unusable for man…
Data-Efficient Generation for Dataset Distillation
Zhe Li, Weitong Zhang, Sarah Cechnicka +1
While deep learning techniques have proven successful in image-related tasks, the exponentially increased data storage and computation costs become a significant challenge. Dataset…
Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics
Weitong Zhang, Chengqi Zang, Liu Li +3
Inverse problems describe the process of estimating the causal factors from a set of measurements or data. Mapping of often incomplete or degraded data to parameters is ill-posed,…