32 citations · 106 across the 33 of their papers we have counts for
4 papers · 1 filter
Targeted Pooled Latent-Space Steganalysis Applied to Generative Steganography, with a Fix
Etienne Levecque, Aurélien Noirault, Tomáš Pevn{ý} +3
Steganographic schemes dedicated to generated images modify the seed vector in the latent space to embed a message. Whereas most steganalysis methods attempt to detect the embeddin…
Distillation of a tractable model from the VQ-VAE
Armin Hadžić, Milan Papez, Tomáš Pevný
Deep generative models with discrete latent space, such as the Vector-Quantized Variational Autoencoder (VQ-VAE), offer excellent data generation capabilities, but, due to the larg…
Sparse Probabilistic Graph Circuits
Martin Rektoris, Milan Papež, Václav Šmídl +1
Deep generative models (DGMs) for graphs achieve impressively high expressive power thanks to very efficient and scalable neural networks. However, these networks contain non-linea…
Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs
Milan Papež, Martin Rektoris, Václav Šmídl +1
Deep generative models (DGMs) have recently demonstrated remarkable success in capturing complex probability distributions over graphs. Although their excellent performance is attr…