Publications of Philipp Kaniuth

Kaniuth, P., & Hebart, M. N. (2022). Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior. NeuroImage, 257. doi:10.1016/j.neuroimage.2022.119294

Kaniuth, P., & Hebart, M. N. (2020). Tuned representational similarity analysis: Improving the fit between computational models of vision and brain data. In Journal of Vision (Vol. 20). Charlottesville, VA: Scholar One, Inc. doi:10.1167/jov.20.11.1076

Hebart, M. N., Perkuhn, J., & Kaniuth, P. Efficiently-generated object similarity scores predicted from human feature ratings and deep neural network activations. Talk_at_event presented at the Annual Meeting of the Vision Science Society (VSS), St. Pete Beach, FL, USA. Retrieved from http://hdl.handle.net/21.11116/0000-000B-2CFA-B

Kaniuth, P., & Hebart, M. N. Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data. Talk_at_event presented at the 10th IMPRS NeuroCom Summer School, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000B-A7CB-4

Kaniuth, P., & Hebart, M. N. Object similarities can be efficiently generated using human ratings and neural network predictions. Poster presented at the 11th IMPRS NeuroCom Summer School, Leipzig, Germany. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2EC-D

Kaniuth, P., Perkuhn, J., & Hebart, M. N. Object similarities can be efficiently generated using human ratings and neural network predictions. Poster presented at the 28th Annual Meeting of the Organization for Human Brain Mapping (OHBM), Glasgow, United Kingdom. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2F0-7

Kaniuth, P., & Hebart, M. N. Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data. Poster presented at the 10th IMPRS NeuroCom Summer School, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2EA-F

Kaniuth, P., & Hebart, M. N. Feature-reweighted RSA: A general purpose method for increasing the fit between vision models and brain data? Poster presented at the Society for Neuroscience Global Connectome, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2F4-3

Kaniuth, P., & Hebart, M. N. Tuned representational similarity analysis: Improving the fit between computational models of vision and brain data. Poster presented at the Vision Sciences Society Annual Meeting 2020, Virtual. Retrieved from http://hdl.handle.net/21.11116/0000-000A-E2EE-B