Publications
Indicative Recent Conference Publications
- Theodoros Christophides, Kyriakos Tolias, and Sotirios Chatzis, “Continual Deep Learning on the Edge via Stochastic Local Competition among Subnetworks,” Proc. ICML Workshops 2024.
- Konstantinos Panousis and Sotirios Chatzis, “DISCOVER: Making Vision Networks Interpretable via Competition and Dissection,” Proc. NeurIPS 2023.
- A. Voskou, K. Panousis, C. Partaourides, K. Tolias, and S. Chatzis, “A New Dataset for End-to-End Sign Language Translation: The Greek Elementary School Dataset,” Proc. ICCV, 2023.
- Konstantinos Kalais and Sotirios Chatzis, “Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning,” Proc. International Conference on Machine Learning (ICML), 2022. (Long Presentation; Acceptance Rate=2%)
- Anastastios Antoniadis, Konstantinos P. Panousis, and Sotirios Chatzis, “Competing Mutual Information Constraints with Stochastic Competition-based Activations for Learning Diversified Representations,” Proc. AAAI Conference on Artificial Intelligence, 2022
- Andreas Voskou, Konstantinos Panousis, Dimitrios Kosmopoulos, Dimitris Metaxas, and Sotirios Chatzis, “Stochastic Transformer Networks with Linear Competing Units: Application to end-to-end SL Translation,” Proc. International IEEE Conference on Computer Vision (ICCV), 2021.
- Konstantinos Panousis, Antonis Alexos, Sergios Theodoridis, and Sotirios Chatzis, “Local Competition and Stochasticity for Adversarial Robustness in Deep Learning,” Proc. 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.
- Konstantinos Panousis*, Sotirios Chatzis*, and Sergios Theodoridis, "Nonparametric Bayesian Local Winner-Takes-All Networks," Proc. International Conference on Machine Learning (ICML), 2019.
Indicative Recent Journal Publications
- Ioannis Stylios, Sotirios Chatzis, Olga Thanou, Spyros Kokolakis, “Continuous Authentication with Feature-Level Fusion of Touch Gestures and Keystroke Dynamics to Solve Security and Usability Issues,” Computers and Security, 2023.
- Lei Cheng, Feng Yin, Sergios Theodoridis, Sotirios Chatzis, and Tsung-Hui Chang, “Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling,” IEEE Signal Processing Magazine, vol. 39, no. 6, pp. 18-52, 2022.
- Anastasios Petropoulos, Vasilios Siakoulis, Panagiotis Lazaris, and Sotirios Chatzis, “Re- constructing the interbank links using machine learning techniques. An application to the Greek Interbank Market,” Intelligent Systems with Applications, vol. 12, 2021.
- Sotirios P. Chatzis, Vasilis Siakoulis, Anastasios Petropoulos, Vangelis Stavroulakis, and Nikos Vlachogiannakis, “Forecasting stock market crisis events using deep and statistical machine learning techniques,” Expert Systems with Applications, vol. 112, pp. 353-371, Dec. 2018.
