Markus Hofmarcher
Markus Hofmarcher
Institute for Machine Learning, Johannes Kepler University Linz
Verified email at
Cited by
Cited by
Speeding up semantic segmentation for autonomous driving
M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ...
Patch Refinement--Localized 3D Object Detection
J Lehner, A Mitterecker, T Adler, M Hofmarcher, B Nessler, S Hochreiter
arXiv preprint arXiv:1910.04093, 2019
Accurate prediction of biological assays with high-throughput microscopy images and convolutional networks
M Hofmarcher, E Rumetshofer, DA Clevert, S Hochreiter, G Klambauer
Journal of chemical information and modeling 59 (3), 1163-1171, 2019
Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks
M Hofmarcher, A Mayr, E Rumetshofer, P Ruch, P Renz, J Schimunek, ...
Available at SSRN 3561442, 2020
Visual scene understanding for autonomous driving using semantic segmentation
M Hofmarcher, T Unterthiner, J Arjona-Medina, G Klambauer, ...
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 285-296, 2019
Human-level protein localization with convolutional neural networks
E Rumetshofer, M Hofmarcher, C Röhrl, S Hochreiter, G Klambauer
International Conference on Learning Representations, 2018
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
VP Patil, M Hofmarcher, MC Dinu, M Dorfer, PM Blies, J Brandstetter, ...
arXiv preprint arXiv:2009.14108, 2020
Artificial neural networks and pathologists recognize basal cell carcinomas based on different histological patterns
S Kimeswenger, P Tschandl, P Noack, M Hofmarcher, E Rumetshofer, ...
Modern Pathology 34 (5), 895-903, 2021
Modern Hopfield Networks for Return Decomposition for Delayed Rewards
M Widrich, M Hofmarcher, VP Patil, A Bitto-Nemling, S Hochreiter
Deep RL Workshop NeurIPS 2021, 2021
Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images
S Kimeswenger, E Rumetshofer, M Hofmarcher, P Tschandl, H Kittler, ...
arXiv preprint arXiv:1911.06616, 2019
Cross-platform end-to-end encryption of contact data for mobile platforms using the example of android
M Hofmarcher, M Strauß, W Narzt
ICWMC 2014, The Tenth International Conference on Wireless and Mobile …, 2014
Estimating Collective Attention toward a Public Display
W Narzt, O Weichselbaum, G Pomberger, M Hofmarcher, M Strauss, ...
ACM Transactions on Interactive Intelligent Systems (TiiS) 8 (3), 1-34, 2018
XAI and Strategy Extraction via Reward Redistribution
MC Dinu, M Hofmarcher, VP Patil, M Dorfer, PM Blies, J Brandstetter, ...
International Workshop on Extending Explainable AI Beyond Deep Models and …, 2022
Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning
K Schweighofer, M Hofmarcher, MC Dinu, P Renz, A Bitto-Nemling, ...
arXiv preprint arXiv:2111.04714, 2021
452 Neural networks detect cutaneous basal cell carcinomas in histological sections
S Kimeswenger, G Klambauer, G Lang, M Hofmarcher, P Tschandl, ...
Journal of Investigative Dermatology 139 (9), S292, 2019
End-to-end learning of pharmacological assays from high-resolution microscopy images
M Hofmarcher, E Rumetshofer, S Hochreiter, G Klambauer
Modern Hopfield Networks for Sample-Efficient Return Decomposition from Demonstrations
M Widrich, M Hofmarcher, V Patil, A Bitto-Nemling, S Hochreiter
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