Publikationen von M Bethge

Akata, E.; Schulz, L.; Coda-Forno, J.; Oh, S.; Bethge, M.; Schulz, E.: Playing repeated games with Large Language Models. Nature Human Behaviour Epub ahead (2025)

Schulze Buschoff, L.; Akata, E.; Bethge, M.; Schulz, E.: Visual cognition in multimodal large language models. Nature Machine Intelligence 7, S. 96 - 106 (2025)

Wallis, T.; Tobias, S.; Bethge, M.; Wichmann, F.: Correction to: Detecting distortions of peripherally presented letter stimuli under crowded conditions. Attention, Perception & Psychophysics 81 (8), S. 2968 - 2970 (2019)

Sinz, F.; Pitkow, X.; Reimer, J.; Bethge, M.; Tolias, A.: Engineering a Less Artificial Intelligence. Neuron 103 (6), S. 967 - 979 (2019)

Cadena, S.; Denfield, G.; Walker, E.; Gatys, L.; Tolias, A.; Bethge, M.; Ecker, A.: Deep convolutional models improve predictions of macaque V1 responses to natural images. PLoS Computational Biology 15 (4), S. 1 - 27 (2019)

Wallis, T.; Funke, C.; Ecker, A.; Gatys, L.; Wichmann, F.; Bethge, M.: Image content is more important than Bouma’s Law for scene metamers. eLife 8, S. 1 - 43 (2019)

Wallis, T.; Funke, C.; Ecker, A.; Gatys, L.; Wichmann, F.; Bethge, M.: Image content is more important than1Bouma’s Law for scene metamers. eLife 8, S. 1 - 43 (2019)

Subramaniyan, M.; Ecker, A.; Patel, S.; Cottonq, R.; Bethge, M.; Pitkow, X.; Berens, P.; Tolias, A.: 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), S. 2430 - 2452 (2018)

Mathis, A.; Mamidanna, P.; Cury, A.; Abe, T.; Murthy, V.; Mathis, M.; Bethge, M.: DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nature Neuroscience 21 (9), S. 1281 - 1289 (2018)

Denfield, G.; Ecker, A.; Shinn, T.; Bethge, M.; Tolias, A.: Attentional fluctuations induce shared variability in macaque primary visual cortex. Nature Communications 9, 2654, S. 1 - 14 (2018)

Gatys, L.; Ecker, A.; Bethge, M.: Texture and art with deep neural networks. Current Opinion in Neurobiology 46, S. 178 - 186 (2017)

Nonnenmacher, M.; Behrens, C.; Berens, P.; Bethge, M.; Macke, J.: Signatures of criticality arise from random subsampling in simple population models. PLoS Computational Biology 13 (10), S. 1 - 23 (2017)

Wallis, T.; Funke, C.; Ecker, A.; Gatys, L.; Wichmann, F.; Bethge, M.: A parametric texture model based on deep convolutional features closely matches texture appearance for humans. Journal of Vision 17 (12), 5, S. 1 - 29 (2017)

Wallis, T.; Tobias, S.; Bethge, M.; Wichmann, F.: Detecting distortions of peripherally presented letter stimuli under crowded conditions. Attention, Perception, Psychophysics 79 (3), S. 850 - 862 (2017)

Franke, K.; Berens, P.; Schubert, T.; Bethge, M.; Euler, T.; Baden, T.: Inhibition decorrelates visual feature representations in the inner retina. Nature 542 (7642), S. 439 - 444 (2017)

Hosseini, R.; Sra, S.; Theis, L.; Bethge, M.: Statistical inference with the Elliptical Gamma Distribution. Computational Statistics & Data Analysis 101, S. 29 - 43 (2016)

Hosseini, R.; Sra, S.; Theis, L.; Bethge, M.: Inference and mixture modeling with the Elliptical Gamma Distribution. Computational Statistics Data Analysis 101, S. 29 - 43 (2016)

Mathis, A.; Rokni, D.; Kapoor, V.; Bethge, M.; Murthy, V.: Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing. Neuron 91 (5), S. 1110 - 1123 (2016)

Theis, L.; Berens, P.; Froudarakis, E.; Reimer, J.; Román Rosón, M.; Baden, T.; Euler, T.; Tolias, A.; Bethge, M.: Benchmarking Spike Rate Inference in Population Calcium Imaging. Neuron 90 (3), S. 471 - 482 (2016)

Wallis, T.; Bethge, M.; Wichmann, F.: Testing models of peripheral encoding using metamerism in an oddity paradigm. Journal of Vision 16 (2), 4, S. 1 - 30 (2016)