Speeding up semantic segmentation for autonomous driving M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ... | 352 | 2016 |
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 | 97 | 2019 |
Patch Refinement--Localized 3D Object Detection J Lehner, A Mitterecker, T Adler, M Hofmarcher, B Nessler, S Hochreiter arXiv preprint arXiv:1910.04093, 2019 | 69 | 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 | 63 | 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 | 60 | 2019 |
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution VP Patil, M Hofmarcher, MC Dinu, M Dorfer, PM Blies, J Brandstetter, ... Proceedings of the 39th International Conference on Machine Learning 162 …, 2022 | 56 | 2022 |
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 | 40 | 2021 |
Understanding the effects of dataset characteristics on offline reinforcement learning K Schweighofer, M Hofmarcher, MC Dinu, P Renz, A Bitto-Nemling, ... Deep RL Workshop NeurIPS 2021, 2021 | 29* | 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 | 26 | 2021 |
Human-level protein localization with convolutional neural networks E Rumetshofer, M Hofmarcher, C Röhrl, S Hochreiter, G Klambauer International conference on learning representations, 2019 | 26 | 2019 |
A Dataset Perspective on Offline Reinforcement Learning K Schweighofer, M Dinu, A Radler, M Hofmarcher, VP Patil, ... Conference on Lifelong Learning Agents, 470-517, 2022 | 23 | 2022 |
Large Language Models Can Self-Improve At Web Agent Tasks A Patel, M Hofmarcher, C Leoveanu-Condrei, MC Dinu, C Callison-Burch, ... arXiv preprint arXiv:2405.20309, 2024 | 14 | 2024 |
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 …, 2020 | 12 | 2020 |
Semantic HELM: A Human-Readable Memory for Reinforcement Learning F Paischer, T Adler, M Hofmarcher, S Hochreiter Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
Learning to Modulate pre-trained Models in RL T Schmied, M Hofmarcher, F Paischer, R Pascanu, S Hochreiter Workshop on Reincarnating Reinforcement Learning at ICLR 2023, 2023 | 7 | 2023 |
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 | 7 | 2019 |
Semantic HELM: An Interpretable Memory for Reinforcement Learning F Paischer, T Adler, M Hofmarcher, S Hochreiter arXiv preprint arXiv:2306.09312, 2023 | 3 | 2023 |
Toward Semantic History Compression for Reinforcement Learning F Paischer, T Adler, A Radler, M Hofmarcher, S Hochreiter Second Workshop on Language and Reinforcement Learning, 2022 | 3 | 2022 |
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 | 2 | 2018 |
Retrieval-Augmented Decision Transformer: External Memory for In-context RL T Schmied, F Paischer, V Patil, M Hofmarcher, R Pascanu, S Hochreiter arXiv preprint arXiv:2410.07071, 2024 | 1 | 2024 |