Publications

Kyle Matoba, Nikolaos Dimitriadis, Francois Fleuret (2023). Benefits of Max Pooling in Neural Networks: Theoretical and Experimental Evidence. Transactions on Machine Learning Research.

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Nikolaos Dimitriadis, Pascal Frossard, Francois Fleuret (2023). Pareto Manifold Learning: Tackling Multiple Tasks via Ensembles of Single-Task Models. International Conference on Machine Learning (ICML).

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Nikolaos Dimitriadis, Francois Fleuret, Pascal Frossard (2023). SequeL: A Continual Learning Library in PyTorch and JAX. CVPR Workshop on Continual Learning 2023 (non-archival track).

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Ahmet Caner Yüzügüler, Nikolaos Dimitriadis, Pascal Frossard (2023). Flexible Channel Dimensions for Differentiable Architecture Search. arXiv (Preprint).

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Ahmet Caner Yüzügüler, Nikolaos Dimitriadis, Pascal Frossard (2022). U-Boost NAS: Utilization-boosted Differentiable Neural Architecture Search. European Conference on Computer Vision (ECCV).

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Nikolaos Dimitriadis, Petros Maragos (2021). Advances in Morphological Neural Networks: Training, Pruning and Enforcing Shape Constraints. ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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Nikolaos Dimitriadis, Petros Maragos (2020). Advances in the Training, Pruning and Enforcement of Shape Constraints of Morphological Neural Networks Using Tropical Algebra. arXiv (Preprint).

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