Machine Learning

M. Avand, A. Kuriqi, M. Khazaei, and O. Ghorbanzadeh (2022) DEM Resolution Effects on Machine Learning Performance for Flood Probability Mapping. Journal of Hydro-environment Research, 40, 1-16, 2022-01-01. (more) (download)

H. Ebrahimy, A. Naboureh, B. Feizizadeh, J. Aryal, and a. O. Ghorbanzadeh (2021) Integration of Sentinel-1 and Sentinel-2 Data with the G-SMOTE Technique for Boosting Land Cover Classification Accuracy. Applied Sciences, 11, 21, 10309, 2021-11-03. (more) (download)

A. Gruca, P. Herruzo, P. Rípodas, A. Kucik, C. Briese, M. K. Kopp, S. Hochreiter, P. Ghamisi, and D. P. Kreil (2021) CDCEO’21 – First Workshop on Complex Data Challenges in Earth Observation. Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 4878–4879, 2021-10-26. (more) (download)

M. Schmitt, C. Persello, G. Vivone, D. Lunga, W. Liao, N. Yokoya, P. Ghamisi, and R. Hänsch (2021) The New Working Groups of the GRSS Technical Committee on Image Analysis and Data Fusion. IEEE Geoscience and Remote Sensing Magazine, 9, 3, 165-166, 2021-09-29. (more) (download)

N. Alinaghi, M. Kattenbeck, A. Golab, and I. Giannopoulos (2021) Will You Take this Turn? Gaze-Based Turning Activity Recognition During Navigation. Leibniz International Proceedings in Informatics (LIPIcs), 11th International Conference on Geographic Information Science (GIScience) - Part 2, 5, 1-16, 2021-09-14. (more) (download)

P. Ghamisi, K. R. Shahi, P. Duan, B. Rasti, S. Lorenz, R. Booysen, S. Thiele, I. C. C. Acosta, M. Kirsch, and R. Gloaguen (2021) The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021-09-01. (more) (download)

C. Shen, M. Krenn, S. Eppel, and A. Aspuru-Guzik (2021) Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations. Machine Learning: Science and Technology, 2, 3, 03LT02, 2021-07-13. (more) (download)

P. A. Robert, R. Akbar, R. Frank, M. Pavlović, M. Widrich, I. Snapkov, M. Chernigovskaya, L. Scheffer, A. Slabodkin, B. B. Mehta, M. Ha Vu, A. Prósz, K. Abram, A. Olar, E. Miho, D. T. T. Haug, F. Lund-Johansen, S. Hochreiter, I. H. Haff, G. Klambauer, G. K. Sandve, and V. Greiff (2021) One Billion Synthetic 3D-Antibody-Antigen Complexes Enable Unconstrained Machine-Learning Formalized Investigation of Antibody Specificity Prediction. bioRxiv, doi:10.1101/2021.07.06.451258, 2021-07-11. (more) (download)

R. Akbar, P. A. Robert, C. R. Weber, M. Widrich, R. Frank, M. Pavlović, L. Scheffer, M. Chernigovskaya, I. Snapkov, A. Slabodkin, B. B. Mehta, E. Miho, F. Lund-Johansen, J. Andersen, S. Hochreiter, I. H. Haff, G. Klambauer, G. K. Sandve, and V. Greiff (2021) In Silico Proof of Principle of Machine Learning-Based Antibody Design at Unconstrained Scale. bioRxiv, doi:10.1101/2021.07.08.451480, 2021-07-09. (more) (download)

S. Mohammed, K. Tai-hoon, P. Ghamisi, and R.-S. Chang (2021) A Special Issue on Recent Progress in Developing Artificial Intelligence and Machine Learning Methodologies. IEEE Geoscience and Remote Sensing Magazine, 9, 2, 7-128, 2021-06-15. (more) (download)

T. Roland, C. Boeck, T. Tschoellitsch, A. Maletzky, S. Hochreiter, J. Meier, and G. Klambauer (2021) Machine Learning Based COVID-19 Diagnosis from Blood Tests with Robustness to Domain Shifts. medRxiv, 2021-04-09. (more) (download)

P. M. Winter, S. Eder, J. Weissenböck, C. Schwald, T. Doms, T. Vogt, S. Hochreiter, and B. Nessler (2021) Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications. arXiv:2103.16910, 2021-03-31. (more) (download)

M. Pavlovic, L. Scheffer, K. Motwani, C. Kanduri, R. Kompova, N. Vazov, K. Waagan, F. LM Bernal, A. A. Costa, B. Corrie, R. Akbar, G. S. Al Hajj, G. Balaban, T. M. Brusko, M. Chernigovskaya, S. Christley, L. G. Cowell, R. Frank, I. Grytten, S. Gundersen, I. H. Haff, S. Hochreiter, E. Hovig, P.-H. Hsieh, G. Klambauer, M. L. Kuijjer, C. Lund-Andersen, A. Martini, T. Minotto, J. Pensar, K. Rand, E. Riccardi, P. A. Robert, A. Rocha, A. Slabodkin, I. Snapkov, L. M. Sollid, D. Titov, C. R. Weber, M. Widrich, G. Yaari, V. Greiff, and G. K. Sandve (2021) immuneML: an Ecosystem for Machine Learning Analysis of Adaptive Immune Receptor Repertoires. bioRxiv, 2021-03-15. (more) (download)

N. Yokoya, P. Ghamisi, R. Hansch, C. Prieur, H. Malha, J. Chanussot, C. Robinson, K. Malkin, and N. Jojic (2021) 2021 Data Fusion Contest: Geospatial Artificial Intelligence for Social Good. IEEE Geoscience and Remote Sensing Magazine, 9, 1, 287-C3, 2021-03-05. (more) (download)

M. Gauch, D. Klotz, F. Kratzert, G. Nearing, S. Hochreiter, and a. J. Lin (2020) A Machine Learner’s Guide to Streamflow Prediction. NeurIPS Workshop: AI for Earth Sciences, 2020-12-12. (more) (download)

A. Mitterecker, A. Hofmann, K. M. Trentino, A. Lloyd, M. F. Leahy, K. Schwarzbauer, T. Tschoellitsch, C. Böck, S. Hochreiter, and J. Meier (2020) Machine learning–based prediction of transfusion. Transfusion, 60, 1977–1986, 2020-06-28. (more) (download)

M. P. Menden, D. Wang, M. J. Mason, B. Szalai, K. C. Bulusu, Y. Guan, T. Yu, J. Kang, M. Jeon, R. Wolfinger, T. Nguyen, M. Zaslavskiy, A.-S. D. C. D. Consortium, I. S. Jang, Z. Ghazoui, M. E. Ahsen, R. Vogel, E. C. Neto, T. Norman, E. K. Y. Tang, M. J. Garnett, G. Y. Di Veroli, S. Fawell, G. Stolovitzky, J. Guinney, J. R. Dry, and J. Saez-Rodriguez (2019) Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nature Communications, 10, 2674, 2019-06-17. (more) (download)

G. Klambauer, S. Hochreiter, and M. Rarey (2019) Machine Learning in Drug Discovery. Journal of Chemical Information and Modeling , 59, 3, 945, 2019-03-25. (more) (download)