Researcher Portfolio

 
   

Ecker, Alexander S

Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, Max Planck Institute for Biological Cybernetics, Max Planck Society, Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society  

 

Researcher Profile

 
Position: Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society
Position: Max Planck Institute for Biological Cybernetics, Max Planck Society
Position: Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society
Additional IDs: MPIKYB: aecker
Researcher ID: https://pure.mpg.de/cone/persons/resource/persons83896

External references

 

Publications

 
  (1 - 25 of 91)
 : Lurz, K.-K., Bashiri, M., Willeke, K., Jagadish, A., Wang, E., Walker, E., Cadena, S., Muhammad, T., Cobos, E., Tolias, A., Ecker, A., & Sinz, F. (2021). Generalization in data-driven models of primary visual cortex. In Ninth International Conference on Learning Representations (ICLR 2021). [PubMan] : Michaelis, C., Weller, M., Funke, C., Ecker, A., Wallis, T., & Bethge, M. (2019). Comparing Search Strategies of Humans and Machines in Clutter. Poster presented at Nineteenth Annual Meeting of the Vision Sciences Society (VSS 2019), St. Pete Beach, FL, USA. doi:10.1167/19.10.309c. [PubMan] : Wallis, T., Funke, C., Ecker, A., Gatys, L., Wichmann, F., & Bethge, M. (2019). Image content is more important than1Bouma’s Law for scene metamers. eLife, 8, 1-43. doi:10.7554/eLife.42512. [PubMan] : Cadena, S., Denfield, G., Walker, E., Gatys, L., Tolias, A., Bethge, M., & Ecker, A. (2019). Deep convolutional models improve predictions of macaque V1 responses to natural images. PLoS Computational Biology, 15(4), 1-27. doi:10.1371/journal.pcbi.1006897. [PubMan] : Wallis, T., Funke, C., Ecker, A., Gatys, L., Wichmann, F., & Bethge, M. (2019). Image content is more important than Bouma’s Law for scene metamers. eLife, 8, 1-43. doi:10.7554/eLife.42512.001. [PubMan] : Ecker, A., Sinz, F., Froudarakis, E., Fahey, P., Cadena, S., Walker, E., Cobos, E., Reimer, J., Tolias, A., & Bethge, M. (2019). A rotation-equivariant convolutional neural network model of primary visual cortex. In Seventh International Conference on Learning Representations (ICLR 2019) (pp. 1-11). [PubMan] : Subramaniyan, M., Ecker, A., Patel, S., Cottonq, R., Bethge, M., Pitkow, X., Berens, P., & Tolias, A. (2018). Faster processing of moving compared with flashed bars in awake macaque V1 provides a neural correlate of the flash lag illusion. Journal of Neurophysiology, 120(5), 2430-2452. doi:10.1152/jn.00792.2017. [PubMan] : Funke, C., Borowski, J., Wallis, T., Brendel, W., Ecker, A., & Bethge, M. (2018). Comparing the ability of humans and DNNs to recognise closed contours in cluttered images. Poster presented at 18th Annual Meeting of the Vision Sciences Society (VSS 2018), St. Pete Beach, FL, USA. [PubMan] : Michaelis, C., Bethge, M., & Ecker, A. (2018). One-Shot Segmentation in Clutter. In J. Dy, & A. Krause (Eds.), International Conference on Machine Learning, 10-15 July 2018, Stockholmsmässan, Stockholm Sweden (pp. 3549-3558). Madison, WI, USA: International Machine Learning Society. [PubMan] : Denfield, G., Ecker, A., Shinn, T., Bethge, M., & Tolias, A. (2018). Attentional fluctuations induce shared variability in macaque primary visual cortex. Nature Communications, 9: 2654, pp. 1-14. doi:10.1038/s41467-018-05123-6. [PubMan] : Cotton, R., Ecker, A., Froudarakis, E., Berens, P., Bethge, M., Saggau, P., & Tolias, A. (2018). Scaling of information in large sensory populations. Poster presented at AREADNE 2018: Research in Encoding And Decoding of Neural Ensembles, Santorini, Greece. [PubMan] : Klindt, D., Ecker, A., Euler, T., & Bethge, M. (2018). Neural system identification for large populations: Separating what and where. Poster presented at AREADNE 2018: Research in Encoding And Decoding of Neural Ensembles, Santorini, Greece. [PubMan] : Klindt, D., Ecker, A., Euler, T., & Bethge, M. (2018). Neural system identification for large populations separating "what" and "where". In I. Guyon, U. von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, & R. Garnett (Eds.), Advances in Neural Information Processing Systems 30 (pp. 3507-3517). Red Hook, NY, USA: Curran. [PubMan] : Wallis, T., Funke, C., Ecker, A., Gatys, L., Wichmann, F., & Bethge, M. (2017). A parametric texture model based on deep convolutional features closely matches texture appearance for humans. Poster presented at 17th Annual Meeting of the Vision Sciences Society (VSS 2017), St. Pete Beach, FL, USA. [PubMan] : Gatys, L., Ecker, A., & Bethge, M. (2017). Texture and art with deep neural networks. Current Opinion in Neurobiology, 46, 178-186. doi:10.1016/j.conb.2017.08.019. [PubMan] : Wallis, T., Funke, C., Ecker, A., Gatys, L., Wichmann, F., & Bethge, M. (2017). A parametric texture model based on deep convolutional features closely matches texture appearance for humans. Journal of Vision, 17(12): 5, pp. 1-29. doi:10.1167/17.12.5. [PubMan] : Klindt, D., Ecker, A., Euler, T., & Bethge, M. (2017). Neural system identification for large populations separating “what” and “where”. Poster presented at Bernstein Conference 2017, Berlin, Germany. doi:10.12751/nncn.bc2017.0132. [PubMan] : Vinogradov, O., Ecker, A., Denfield, G., Tolias, A., & Bethge, M. (2017). Mixed latent variable model of attention in V1. Poster presented at Bernstein Conference 2017, Berlin, Germany. doi:10.12751/nncn.bc2017.0210. [PubMan] : Wallis, T., Funke, C., Ecker, A., Gatys, L., Wichmann, F., & Bethge, M. (2017). Towards matching peripheral appearance for arbitrary natural images using deep features. Poster presented at 17th Annual Meeting of the Vision Sciences Society (VSS 2017), St. Pete Beach, FL, USA. [PubMan] : Gatys, L., Ecker, A., Bethge, M., Hertzmann, A., & Shechtman, B. (2017). Controlling Perceptual Factors in Neural Style Transfer. In 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) (pp. 3730-3738). Piscataway, NJ, USA: IEEE. [PubMan] : Denfield, G., Ecker, A., & Tolias, A. (2017). The Role of Internal Signals in Structuring V1 Population Activity. Poster presented at 27th Annual Rush and Helen Record Neuroscience Forum, Galveston, TX, USA. [PubMan] : Cadena, S., Ecker, A., Denfield, G., Walker, E., Tolias, A., & Bethge, M. (2017). A goal-driven deep learning approach for V1 system identification. Poster presented at Computational and Systems Neuroscience Meeting (COSYNE 2017), Salt Lake City, UT, USA. [PubMan] : Wallis, T., Funke, C., Ecker, A., Gatys, L., Wichmann, F., & Bethge, M. (2016). Towards matching the peripheral visual appearance of arbitrary scenes using deep convolutional neural networks. Perception, 45(ECVP Abstract Supplement), 175-176. [PubMan] : Cadena, S., Ecker, A., Denfield, G., Walker, E., Tolias, A., & Bethge, M. (2016). A goal-driven deep learning approach for V1 system identification. Poster presented at Bernstein Conference 2016, Berlin, Germany. [PubMan] : Wallis, T., Ecker, A., Gatys, L., Funke, C., Wichmann, F., & Bethge, M. (2016). Seeking summary statistics that match peripheral visual appearance using naturalistic textures generated by Deep Neural Networks. Poster presented at 16th Annual Meeting of the Vision Sciences Society (VSS 2016), St. Pete Beach, FL, USA. [PubMan]