Klaus Obermayer
Photo: SCIoI
Klaus Obermayer and his research group study the principles which underlie information processing in neural and artificial systems. Current projects cover the three thematic areas Models of neural systems, machine learning and artificial neural networks, and the analysis of neural data. Klaus Obermayer will contribute to SCoI mainly with his expertise in machine learning for pattern recognition, reinforcement learning, and the computational modelling of human perception, decision making, and reward-based learning.
Projects
Klaus Obermayer is member of:
• Project 01: Object-level scene descriptions and attention in visual search
• Project 15: Efficient Multi-task Deep Learning
• Project 57: Internal and External Visual Information Sampling Using Eye-Movements and Overt Attention in Dynamic Scenes
• Project 15: Efficient Multi-task Deep Learning
• Project 57: Internal and External Visual Information Sampling Using Eye-Movements and Overt Attention in Dynamic Scenes
Publications +
Roth, N., McLaughlin, J., Obermayer, K., & Rolfs, M. (2024). Gaze Behavior Reveals Expectations of Potential Scene Changes. Psychological Science, 35(12), 1350–1363. https://doi.org/10.1177/09567976241279198
Hall, O., Qu, R., Ouerfelli-Ethier, J., Roth, N., Hellwich, O., Obermayer, K., & Rolfs, M. (2024). Saccadic decision-making in dynamic scenes under competing task demands. EGPROC.
Roth, N., Rolfs, M., Hellwich, O., & Obermayer, K. (2023). Objects guide human gaze behavior in dynamic real-world scenes. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1011512
Roth, N., Shurygina, O., Muscinelli, F. M., Obermayer, K., & Rolfs, M. (2023). Modeling the spread of object-based attention during free viewing. MODVIS 2023. https://docs.lib.purdue.edu/modvis/2023/session02/3/
Roth, N., McLaughlin, J., Obermayer, K., & Rolfs, M. (2023). Looking for potential action: Differences in exploration behavior of static and (potentially) dynamic scenes. Journal of Vision. https://doi.org/10.1167/jov.23.9.5293
Roth, N., Rolfs, M., & Obermayer, K. (2022). ScanDy: Simulating Realistic Human Scanpaths in Dynamic Real-World Scenes. MODVIS 2022. https://docs.lib.purdue.edu/modvis/2022/session01/6/
Roth, N., Rolfs, M., & Obermayer, K. (2022). Scanpath prediction in dynamic real-world scenes based on object-based selection. Journal of Vision / VSS 2022. https://doi.org/10.1167/jov.22.14.4217
Muscinelli, F., Roth, N., Shurygina, O., Obermayer, K., & Rolfs, M. (2022). Object-based Spread of Attention Affects Fixation Duration During Free Viewing. PERCEPTION / 44th European Conference on Visual Perception (ECVP) 2022. https://journals.sagepub.com/doi/10.1177/03010066221141167
Chouzouris, T., Roth, N., Cakan, C., & Obermayer, K. (2021). Applications of optimal nonlinear control to a whole-brain network of FitzHugh-Nagumo oscillators. Physical Review E, 104(2), 24213. https://doi.org/10.1103/PhysRevE.104.024213
Roth, N., Bideau, P., Hellwich, O., Rolfs, M., & Obermayer, K. (2021). Modeling the influence of objects on saccadic decisions in dynamic real-world scenes. PERCEPTION / 43rd European Conference on Visual Perception (ECVP) 2021. https://journals.sagepub.com/doi/full/10.1177/03010066211059887
Roth, N., Bideau, P., Hellwich, O., Rolfs, M., & Obermayer, K. (2021). A modular framework for object-based saccadic decisions in dynamic scenes. CVPR EPIC Workshop / ArXiv:2106.06073. https://doi.org/10.48550/arXiv.2106.06073
TU Intern – June 2021 - Wo der Sinn von Wörtern und Sätzen sein Zuhause hat
