B. Psomas, I. Kakogeorgiou, K. Karantzalos, and Y. Avrithis (2023) Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?. arXiv:2309.06891, 2023-09-13. (more) (download)

A. Jamali, S. K. Roy, J. Li, and P. Ghamisi (2023) Neighborhood Attention Makes the Encoder of ResUNet Stronger for Accurate Road Extraction. arXiv:2306.04947, 2023-06-08. (more) (download)

A. Jamali, S. K. Roy, and P. Ghamisi (2023) WetMapFormer: A Unified Deep CNN and Vision Transformer for Complex Wetland Mapping. International Journal of Applied Earth Observation and Geoinformation, 120, 103333, 2023-06-01. (more) (download)

J. Schimunek, P. Seidl, L. Friedrich, D. Kuhn, F. Rippmann, S. Hochreiter, and G. Klambauer (2023) Context-Enriched Molecule Representations Improve Few-Shot Drug Discovery. arXiv:2305.09481, 2023-04-24. (more) (download)

S. Chang & P. Ghamisi (2023) Changes to Captions: An Attentive Network for Remote Sensing Change Captioning. arXiv:2304.01091, 2023-04-03. (more) (download)

A. Jamali, S. K. Roy, A. Bhattacharya, and P. Ghamisi (2023) Local Window Attention Transformer for Polarimetric SAR Image Classification. IEEE Geoscience and Remote Sensing Letters, 2023-01-23. (more) (download)

C. H. Song, J. Yoon, S. Choi, and Y. Avrithis (2023) Boosting Vision Transformers for Image Retrieval. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 107-117, 2023-01-03. (more) (download)


I. Kakogeorgiou, S. Gidaris, B. Psomas, Y. Avrithis, A. Bursuc, K. Karantzalos, and N. Komodakis (2022) What to Hide from Your Students: Attention-Guided Masked Image Modeling. arXiv:2203.12719v2, 2022-07-22. (more) (download)

M. Mc Cutchan & I. Giannopoulos (2022) Encoding Geospatial Vector Data for Deep Learning: LULC as a Use Case. Remote Sensing, 14, 12, 2812, 2022-06-11. (more) (download)


F. Tang & M. Kopp (2021) A Remark on a Paper of Krotov and Hopfield. arXiv:2105.15034, 2021-06-03. (more) (download)


H. Ramsauer, B. Schäfl, J. Lehner, P. Seidl, M. Widrich, L. Gruber, M. Holzleitner, M. Pavlović, G. K. Sandve, V. Greiff, D. Kreil, M. Kopp, G. Klambauer, J. Brandstetter, and S. Hochreiter (2020) Hopfield Networks is All You Need. arXiv:2008.02217, 2020-08-06. (more) (download)

M. Widrich, B. Schäfl, H. Ramsauer, M. Pavlović, L. Gruber, M. Holzleitner, J. Brandstetter, G. K. Sandve, V. Greiff, S. Hochreiter, and G. Klambauer (2020) Modern Hopfield Networks and Attention for Immune Repertoire Classification. arXiv:2007.13505, 2020-07-16. (more) (download)


S. Kimeswenger, E. Rumetshofer, M. Hofmarcher, P. Tschandl, H. Kittler, S. Hochreiter, W. Hötzenecker, and G. Klambauer (2019) Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images. ML4H: Machine Learning for Health workshop at NeurIPS 2019, Vancouver, 10-12 Dec 2019, or preprint at arXiv, 1911.06616v3, Image and Video Processing (eess.IV), 2019-12-02. (more) (download)


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