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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 …
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 …
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 …
(and including) optimal transport. Theoretically, the focus is on fitting a large class of …
Factorization approach for sparse spatio-temporal brain-computer interface
Recently, advanced technologies have unlimited potential in solving various problems with
a large amount of data. However, these technologies have yet to show competitive …
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 …
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 …
hat mich Michaels Begeisterung für Mathematik stets angesteckt. Er hat sich immer Zeit …