| 2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets Proceedings of Machine Learning Research 176, 2022 | 50* | 2022 |
| EEGminer: Discovering Interpretable Features of Brain Activity with Learnable Filters S Ludwig, S Bakas, DA Adamos, N Laskaris, Y Panagakis, S Zafeiriou Journal of Neural Engineering 21 (3), 036010, 2024 | 20 | 2024 |
| Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition S Bakas, S Ludwig, K Barmpas, M Bahri, Y Panagakis, N Laskaris, ... arXiv preprint arXiv:2202.03267, 2022 | 14 | 2022 |
| Latent alignment in deep learning models for EEG decoding S Bakas, S Ludwig, DA Adamos, N Laskaris, Y Panagakis, S Zafeiriou Journal of Neural Engineering 22 (1), 016047, 2025 | 9* | 2025 |
| Using Natural Language Processing Techniques to Tackle the Construct Identity Problem in Information Systems Research S Ludwig, B Funk, B Mueller Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020 | 7 | 2020 |
| Stochastic Resonance Improves the Detection of Low Contrast Images in Deep Learning Models S Ludwig arXiv preprint arXiv:2502.14442, 2019 | 1 | 2019 |
| EEG-D3: A Solution to the Hidden Overfitting Problem of Deep Learning Models S Ludwig, S Bakas, K Barmpas, G Zoumpourlis, DA Adamos, N Laskaris, ... arXiv preprint arXiv:2512.13806, 2025 | | 2025 |
| Learnable Filters for EEG Classification D Adamos, N Laskaris, S Zafeiriou, S Ludwig, S Bakas WO Patent WO/2023/007,118, 2023 | | 2023 |
| Geometric Deep Learning for the Prediction of Music Liking from Consumer-Grade EEG S Ludwig Radboud University Nijmegen, 2020 | | 2020 |
| A spiking neuron implementation of genetic algorithms for optimization S Ludwig, J Hartjes, B Pol, G Rivas, J Kwisthout Cao, L.; Kosters, W.; Lijffijt, J.(ed.), Proceedings of the 32nd Benelux …, 2020 | | 2020 |
Nikos LaskarisProfessor, Department of Informatics, AUTHVerified email at aiia.csd.auth.gr
