2 citations · 2 across the 5 of their papers we have counts for
5 papers
DISCOVER: Making Vision Networks Interpretable via Competition and Dissection
Konstantinos P. Panousis, Sotirios Chatzis
Modern deep networks are highly complex and their inferential outcome very hard to interpret. This is a serious obstacle to their transparent deployment in safety-critical or bias-…
A New Dataset for End-to-End Sign Language Translation: The Greek Elementary School Dataset
Andreas Voskou, Konstantinos P. Panousis, Harris Partaourides +2
Automatic Sign Language Translation (SLT) is a research avenue of great societal impact. End-to-End SLT facilitates the interaction of Hard-of-Hearing (HoH) with hearing people, th…
Macroeconomic forecasting and sovereign risk assessment using deep learning techniques
Anastasios Petropoulos, Vassilis Siakoulis, Konstantinos P. Panousis +2
In this study, we propose a novel approach of nowcasting and forecasting the macroeconomic status of a country using deep learning techniques. We focus particularly on the US econo…
Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning
Konstantinos Kalais, Sotirios Chatzis
This work addresses meta-learning (ML) by considering deep networks with stochastic local winner-takes-all (LWTA) activations. This type of network units results in sparse represen…
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial Robustness
Konstantinos P. Panousis, Sotirios Chatzis, Sergios Theodoridis
This work explores the potency of stochastic competition-based activations, namely Stochastic Local Winner-Takes-All (LWTA), against powerful (gradient-based) white-box and black-b…