Multi-student Diffusion Distillation for Better One-step Generators

Y Song, J Lorraine, W Nie, K Kreis, J Lucas - arxiv preprint arxiv …, 2024‏ - arxiv.org
Diffusion models achieve high-quality sample generation at the cost of a lengthy multistep
inference procedure. To overcome this, diffusion distillation techniques produce student …

A novel generative adversarial network-based approach for automated brain tumour segmentation

R Sille, T Choudhury, A Sharma, P Chauhan, R Tomar… - Medicina, 2023‏ - mdpi.com
Background: Medical image segmentation is more complicated and demanding than
ordinary image segmentation due to the density of medical pictures. A brain tumour is the …

Minmax methods for optimal transport and beyond: Regularization, approximation and numerics

L De Gennaro Aquino… - Advances in Neural …, 2020‏ - proceedings.neurips.cc
We study MinMax solution methods for a general class of optimization problems related to
(and including) optimal transport. Theoretically, the focus is on fitting a large class of …

Factorization approach for sparse spatio-temporal brain-computer interface

BH Lee, JH Cho, BH Kwon… - 2022 26th International …, 2022‏ - ieeexplore.ieee.org
Recently, advanced technologies have unlimited potential in solving various problems with
a large amount of data. However, these technologies have yet to show competitive …

3D Brain Tumor Segmentation on U-Net Classifier

GP Suja, P Kaleeswari, P Raajan… - … Computing and Data …, 2023‏ - ieeexplore.ieee.org
For deep learning segmentation approaches, it can be difficult to extract the multimodal
features that are present in multimodal glioma pictures, which provide a variety of aspects of …

Uncertainty and stochastic optimization: numerical methods, regularization and asymptotic analysis

S Eckstein - 2020‏ - kops.uni-konstanz.de
Zunächst danke ich meinem Betreuer Michael Kupper. Von Beginn meiner Masterarbeit an
hat mich Michaels Begeisterung für Mathematik stets angesteckt. Er hat sich immer Zeit …