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Found 4 papers, 1 papers with code
DP$^2$-VAE: Differentially Private Pre-trained Variational Autoencoders
Similar to other differentially private (DP) learners, the major challenge for DPGM is also how to achieve a subtle balance between utility and privacy.
Revisiting flow generative models for Out-of-distribution detection
Deep generative models have been widely used in practical applications such as the detection of out-of-distribution (OOD) data.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Conditional Generative Quantile Networks via Optimal Transport and Convex Potentials
Quantile regression has a natural extension to generative modelling by leveraging a stronger convergence in pointwise rather than in distribution.
Multi-Scale Supervised 3D U-Net for Kidneys and Kidney Tumor Segmentation
We present a multi-scale supervised 3D U-Net, MSS U-Net, to automatically segment kidneys and kidney tumors from CT images.
