Publikationen von Philipp Kaniuth

Zeitschriftenartikel (1)

2022
Zeitschriftenartikel
Kaniuth, P.; Hebart, M. N.: Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior. NeuroImage 257, 119294 (2022)

Meeting Abstract (1)

2020
Meeting Abstract
Kaniuth, P.; Hebart, M. N.: Tuned representational similarity analysis: Improving the fit between computational models of vision and brain data. In Journal of Vision, 20, 1076. Vision Sciences Society Annual Meeting 2020, 19. Juni 2020 - 24. Juni 2020. Scholar One, Inc., Charlottesville, VA (2020)

Vortrag (2)

2022
Vortrag
Hebart, M. N.; Perkuhn, J.; Kaniuth, P.: Efficiently-generated object similarity scores predicted from human feature ratings and deep neural network activations. Annual Meeting of the Vision Science Society (VSS), St. Pete Beach, FL, USA (2022)
2021
Vortrag
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 (5)

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)
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
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
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)
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