Publications of Martin N. Hebart

Talk (10)

2021
Talk
Hebart, M. N.: Revealing interpretable representations in artificial and biological vision. Japanese Meeting for Human Brain Imaging, National Institute for Physiological Sciences, Okazaki, Japan (2021)
Talk
Hebart, M. N.: Revealing the similarities and differences between object representations in humans and DNNs. Tagung experimentell arbeitender Psychologen (TeaP), Ulm, Germany (2021)
2020
Talk
Hebart, M. N.: THINGS: A large-scale global initiative to study the cognitive, computational, and neural mechanisms of object recognition in biological and artificial intelligence. NeurIPS workshop “Shared Visual Representations in Human & Machine Intelligence”, Virtual (2020)
Talk
Hebart, M. N.; Zheng, C.; Pereira, F.; Baker, C.: Revealing the multidimensional mental representations of natural objects. Neuromatch 2.0, Virtual (2020)

Poster (15)

2022
Poster
Mahner, F.; Seeliger, K.; Umut, G.; Hebart, M. N.: Learning cortical magnification with brain-optimized convolutional neural networks. Conference on Cognitive Computational Neuroscience, San Francisco, CA, USA (2022)
Poster
Hebart, M. N.; Contier, O.; Baker, C.I.; Teichmann, L.: The THINGS initiative: A global large-scale effort for the representative study of objects in brains, behavior, and computational models. 47. Jahrestagung Psychologie und Gehirn 2022, Freiburg, Germany (2022)
Poster
Kaniuth, P.; Hebart, M. N.: Object similarities can be efficiently generated using human ratings and neural network predictions. 11th IMPRS NeuroCom Summer School, Leipzig, Germany (2022)
Poster
Kaniuth, P.; Perkuhn, J.; Hebart, M. N.: Object similarities can be efficiently generated using human ratings and neural network predictions. 28th Annual Meeting of the Organization for Human Brain Mapping (OHBM), Glasgow, United Kingdom (2022)
Poster
Hansen, H.; Hebart, M. N.: Automatic generation of semantic feature norms of objects using GPT-3. Annual Meeting of the Vision Science Society (VSS), St. Pete Beach, FL, USA (2022)
Poster
Stoinski, L.; Perkuhn, J.; Hebart, M. N.: THINGS+: New norms and metadata for the THINGS database of 1,854 object concepts and 26,107 natural object images. Vision Science Society Congress, St. Pete Beach, FL, USA (2022)
Poster
Contier, O.; Dickter, A. H.; Teichmann , L.; Hebart, M. N.: THINGS-fMRI/MEG: A large-scale multimodal neuroimaging dataset of responses to natural object images. Vision Sciences Society Annual Meeting (V-VSS), Virtual (2022)
Poster
Contier, O.; Hebart, M. N.: Distributed representation of behaviorally-relevant object dimensions in the human brain. Vision Sciences Society Annual Meeting (VSS), St. Pete Beach, FL, USA (2022)
2021
Poster
Contier, O.; Hebart, M. N.; Dickter, A. H.; Teichmann, L.; Kidder, A.; Corriveau, A.; Zheng, C.; Vaziri-Pashkam, M.; Baker, C. I.: THINGS-fMRI/MEG: A densely sampled multimodal neuroimaging dataset of brain responses to a broad range of natural object images. Society for Neuroscience 50th Annual Meeting, Virtual (2021)
Poster
Kaniuth, P.; Hebart, M. N.: Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data. 10th IMPRS NeuroCom Summer School, Virtual (2021)
Poster
Contier, O.; Hebart, M. N.; Dickter, A. H.; Teichmann, L.; Kidder, A.; Corriveau, A.; Zheng, C.; Vaziri-Pashkam, M.; Baker, C. I.: THINGS-fMRI/MEG: A large-scale multimodal neuroimaging dataset of responses to natural object images. Vision Sciences Society Annual Meeting (V-VSS), Virtual (2021)
Poster
Roth, J.; Seeliger, K.; Schmid, T.; Hebart, M. N.: Preferred stimuli for individual voxels in the human visual system. 2021 Computational and Systems Neuroscience (Cosyne), Virtual (2021)
Poster
Kaniuth, P.; Hebart, M. N.: Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data? Society for Neuroscience Global Connectome, Virtual (2021)
2020
Poster
Singer, J.; Seeliger, K.; Hebart, M. N.: The representation of object drawings and sketches in deep convolutional neural networks. NeurIPS Workshop SVRHM, Virtual (2020)
Poster
Kaniuth, P.; Hebart, M. N.: Tuned representational similarity analysis: Improving the fit between computational models of vision and brain data. Vision Sciences Society Annual Meeting 2020, Virtual (2020)

Preprint (14)

2022
Preprint
Schmidt, F.; Hebart, M. N.; Schmid, A. a. C.; Fleming, R. W.: Core dimensions of human material perception. (2022)
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