Search Results for author:
Found 7 papers, 1 papers with code
FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transforms
Medical image segmentation is a crucial task that relies on the ability to accurately identify and isolate regions of interest in medical images.
LoRA-Ensemble: Efficient Uncertainty Modelling for Self-attention Networks
We introduce LoRA-Ensemble, a parameter-efficient deep ensemble method for self-attention networks, which is based on Low-Rank Adaptation (LoRA).
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection
We propose a novel approach to video anomaly detection: we treat feature vectors extracted from videos as realizations of a random variable with a fixed distribution and model this distribution with a neural network.
Majorization-Minimization for sparse SVMs
Several decades ago, Support Vector Machines (SVMs) were introduced for performing binary classification tasks, under a supervised framework.
Score-Based Generative Models for Medical Image Segmentation using Signed Distance Functions
Medical image segmentation is a crucial task that relies on the ability to accurately identify and isolate regions of interest in medical images.
Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging
The proposed method employs estimates of the posterior variance together with techniques from conformal prediction in order to obtain coverage guarantees for the error bounds, without making any assumption on the underlying data distribution.
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction
To this end, we solve the linear inverse problem of undersampled MRI reconstruction in a variational setting.
