Heiko H Schütt, PhD

2018-2023 Center for Neural Science New York University, New York, NY, United States 
 2023- Cognitive Science and Assessment Group Universität Luxemburg 
Vision, Computational Models, Evaluation Methods
"Heiko Schütt"
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Golan T, Taylor J, Schütt H, et al. (2023) Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses. The Behavioral and Brain Sciences. 46: e392
Kuperwajs I, Schütt HH, Ma WJ. (2023) Using deep neural networks as a guide for modeling human planning. Scientific Reports. 13: 20269
Schütt HH, Kipnis AD, Diedrichsen J, et al. (2023) Statistical inference on representational geometries. Elife. 12
Schütt HH, Yoo AH, Calder-Travis J, et al. (2023) Point estimate observers: A new class of models for perceptual decision making. Psychological Review
Flachot A, Akbarinia A, Schütt HH, et al. (2022) Deep neural models for color classification and color constancy. Journal of Vision. 22: 17
Schütt HH, Rothkegel LOM, Trukenbrod HA, et al. (2019) Disentangling bottom-up versus top-down and low-level versus high-level influences on eye movements over time. Journal of Vision. 19: 1
Rothkegel LOM, Schütt HH, Trukenbrod HA, et al. (2019) Searchers adjust their eye-movement dynamics to target characteristics in natural scenes. Scientific Reports. 9: 1635
Schütt H, Rothkegel L, Trukenbrod H, et al. (2018) Predicting fixation densities over time from early visual processing Journal of Vision. 18: 1210
Rothkegel LOM, Trukenbrod HA, Schütt HH, et al. (2017) Temporal evolution of the central fixation bias in scene viewing. Journal of Vision. 17: 3
Schütt HH, Wichmann FA. (2017) An image-computable psychophysical spatial vision model. Journal of Vision. 17: 12
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