Singer, J.; Seeliger, K.; Hebart, M. N.: The representation of object drawings and sketches in deep convolutional neural networks. NeurIPS Workshop SVRHM, Virtual (2020)

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)

Linde-Domingo, J.; Ortiz-Tudela, J.; Völler, J.; Hebart, M. N.; González-García, C.: Determinants of visual ambiguity resolution. bioRxiv (2025)

Nortmann, T.; Sulewski, P.; Kietzmann, T. C.: Predictive remapping and allocentric coding as consequences of energy efficiency in recurrent neural network models of active vision. bioRxiv (2025)

Kaemmer, L.; Kroell, L. M.; Knapen, T.; Rolfs, M.; Hebart, M. N.: Feedback of peripheral saccade targets to early foveal cortex. bioRxiv (2025)

Teichmann, L.; Hebart, M. N.; Baker, C. I.: Dynamic representation of multidimensional object properties in the human brain. bioRxiv (2025)

Kaniuth, P.; Mahner, F.; Perkuhn, J.; Hebart, M. N.: A high-throughput approach for the efficient prediction of perceived similarity of natural objects. bioRxiv (2024)

Amme, C.; Sulewski, P.; Spaak, E.; Hebart, M. N.; König, P.; Kietzmann, T. C.: Saccade onset, not fixation onset, best explains early sensory responses across the human visual cortex during naturalistic vision. bioRxiv (2024)

Hofmann, S.; Ciston, A.; Koushik, A.; Klotzsche, F.; Hebart, M. N.; Müller, K.-R.; Villringer, A.; Scherf, N.; Hilsmann, A.; Nikulin, V. V. et al.; Gaebler, M.: Human-aligned deep and sparse encoding models of dynamic 3D face similarity perception. PsyArXiv (2024)

Contier, O.; Baker, C. I.; Hebart, M. N.: Distributed representations of behavior-derived object dimensions in the human visual system. bioRxiv (2024)

van Bree, S.; Mackenzie, A. S.; Wimber, M.: No evidence that visual impulses enhance the readout of retrieved long-term memory contents from EEG activity. bioRxiv (2024)

Muttenthaler, L.; Zheng, C. Y.; McClure, P.; Vandermeulen, R. A.; Hebart, M. N.; Pereira, F.: VICE: Variational Interpretable Concept Embeddings. arXiv (2022)

Seeliger, K.; Güçlü, U.; Le, L.; Güçlütürk, Y.; van Gerven, M.: Brain2Pix: Fully convolutional naturalistic video reconstruction from brain activity. bioRxiv (2021)