no code implementations • 13 Jul 2023 • Mohammad Adiban, Kalin Stefanov, Sabato Marco Siniscalchi, Giampiero Salvi
We address the video prediction task by putting forth a novel model that combines (i) our recently proposed hierarchical residual vector quantized variational autoencoder (HR-VQVAE), and (ii) a novel spatiotemporal PixelCNN (ST-PixelCNN).
1 code implementation • 9 Aug 2022 • Mohammad Adiban, Kalin Stefanov, Sabato Marco Siniscalchi, Giampiero Salvi
We propose a multi-layer variational autoencoder method, we call HR-VQVAE, that learns hierarchical discrete representations of the data.
no code implementations • 11 Sep 2020 • Mohammad Adiban, Arash Safari, Giampiero Salvi
In this study, we introduce a novel unsupervised countermeasure for smart grid power systems, based on generative adversarial networks (GANs).
no code implementations • 26 Apr 2019 • Mohammad Adiban, Bagher BabaAli, Saeedreza Shehnepoor
In this study, an approach is proposed for normal/abnormal heart sound classification on the Physionet challenge 2016 dataset.