20 citations · 26 across the 8 of their papers we have counts for
5 papers · 1 filter
WeLa-VAE: Learning Alternative Disentangled Representations Using Weak Labels
Vasilis Margonis, Athanasios Davvetas, Iraklis A. Klampanos
Learning disentangled representations without supervision or inductive biases, often leads to non-interpretable or undesirable representations. On the other hand, strict supervisio…
Unsupervised Severe Weather Detection Via Joint Representation Learning Over Textual and Weather Data
Athanasios Davvetas, Iraklis A. Klampanos
When observing a phenomenon, severe cases or anomalies are often characterised by deviation from the expected data distribution. However, non-deviating data samples may also implic…
Learning Improved Representations by Transferring Incomplete Evidence Across Heterogeneous Tasks
Athanasios Davvetas, Iraklis A. Klampanos
Acquiring ground truth labels for unlabelled data can be a costly procedure, since it often requires manual labour that is error-prone. Consequently, the available amount of labell…
Evidence Transfer for Improving Clustering Tasks Using External Categorical Evidence
Athanasios Davvetas, Iraklis A. Klampanos, Vangelis Karkaletsis
In this paper we introduce evidence transfer for clustering, a deep learning method that can incrementally manipulate the latent representations of an autoencoder, according to ext…
Autoencoder-Driven Weather Clustering for Source Estimation during Nuclear Events
I. A. Klampanos, A. Davvetas, S. Andronopoulos +3
Emergency response applications for nuclear or radiological events can be significantly improved via deep feature learning due to the hidden complexity of the data and models invol…