S. Trick, C. A Rothkopf, F. Jaekel. A normative model for Bayesian combination of subjective probability estimates, Judgment and Decision Making, [accepted].

M. Raab, L. Voigt, C. Rothkopf, K. Fiehler. Studying naturalistic actions requires research programs and not trade-off decisions in individual studies. Commentary to Maselli, A. et al.: Beyond simple laboratory studies: Developing sophisticated models to study rich behavior, Physics of Life Reviews, [accepted].

Trick, S., Lott, V., Scherf, L., Rothkopf, C. A., Koert, D. What can I help you with: towards task-independent detection of intentions for interaction in a human-robot environment. IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), [accepted].

F. Tatai, D. Straub, C. A. Rothkopf. People use Newtonian physics in intuitive sensorimotor decisions under risk, Annual Meeting of the Cognitive Science Society, 2023.
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F. Kadner, H. Willkomm, I. Ibs, C. A. Rothkopf. Finding your way out: planning strategies in human maze-solving behavior, Annual Meeting of the Cognitive Science Society, 2023.
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PsyArXiv, 2022 [] html

F. Kadner, T. Thomas, D. Hoppe, C. A Rothkopf. Improving saliency models' predictions of the next fixation with humans' intrinsic cost of gaze shifts, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023
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arXiv, 2022 [] html

S. Trick, C. A. Rothkopf. Bayesian classifier fusion with an explicit model of correlation, International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 151:2282-2310, 2022
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arXiv, 2021 [] html

S. Trick, D. Koert, J. Peters, C. Rothkopf. Multimodal uncertainty reduction for intention recognition in human-robot interaction. International Conference on Intelligent Robots and Systems (IROS), 2019
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D. Koert, J. Pajarinen, A. Schotschneider, S. Trick, C. Rothkopf, J. Peters. Learning intention aware online adaptation of movement primitives. IEEE Robotics and Automation Letters (RA-L), with presentation at the IEEE International Conference on Intelligent Robots and Systems (IROS), 2019
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N. Araslanov, C. A. Rothkopf, S. Roth. Actor-critic instance segmentation. Conference on Computer Vision and Pattern Recognition (CVPR), 2019
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arXiv, 2019
https://arxiv.org/abs/1904.05126

D. Hoppe, S. Helfmann, C. A. Rothkopf. Humans quickly learn to blink strategically in response to environmental task demands. Proceedings of the National Academy of Sciences (PNAS), 2018
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V. S. R. Veeravasarapu, C. A. Rothkopf, V. Ramesh: 'Adversarially tuned scene generation', Conference on Computer Vision and Pattern Recognition (CVPR), 2017
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V. S. R. Veeravasarapu, C. A. Rothkopf, V. Ramesh: 'Model-driven simulations for computer vision', IEEE Winter Conference on Applications of Computer Vision (WACV), 2017
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B. Belousov, G. Neumann, C. A. Rothkopf, J. Peters: 'Catching heuristics are optimal control policies', Proceedings of the Annual Conference on Neural Information Processing Systems (NIPS), 2016
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C. A. Rothkopf, D. H. Ballard: 'Modular inverse reinforcement learning for visuomotor behavior', Biological Cybernetics, 107(4), 477-490, 2013 (wird in neuem Tab geöffnet) [pdf] [html]

D. H. Ballard, D. Kit, C. A. Rothkopf, B. Sullivan: 'A hierarchical modular architecture for embodied cognition', Multisensory Research, 26:(1-2), 177 – 204 (wird in neuem Tab geöffnet) [pdf] [html]

D. Pamplona, J. Triesch, C. A. Rothkopf: 'Power spectra of the natural input to the visual system', Vision Research, 83:66-75, 2013 (wird in neuem Tab geöffnet) [pdf] [html]

Y. Zhao, C. A. Rothkopf, J. Triesch, B. Shi: 'A unified model of the joint development of disparity selectivity and vergence control', IEEE 8th International Conference on Development and Learning, November 7-9, 2012 (Paper of Excellence award) (wird in neuem Tab geöffnet) [pdf] [html]

C. Dimitrakakis, C. A. Rothkopf: 'Bayesian multitask inverse reinforcement learning', European Workshop on Reinforcemnt Learning (EWRL), September 9–11, 2011 (wird in neuem Tab geöffnet) [pdf] [html]

C. A. Rothkopf, C. Dimitrakakis: 'Preference elicitation and inverse reinforcement learning', 22nd European Conference on Machine Learning (ECML), September 5-9, 2011 (wird in neuem Tab geöffnet) [pdf] [html]

H. Toutounji, C. A. Rothkopf, J. Triesch: 'Scalable reinforcement learning through hierarchical decompositions for weakly-coupled problems', IEEE 10th International Conference on Development and Learning (ICDL), August 24-27, 2011 (wird in neuem Tab geöffnet) [pdf] [html]

C. Karaoguz, T. H. Weisswange, T. Rodemann, B. Wrede, C. A. Rothkopf: 'Reward-based learning of optimal cue integration in audio and visual depth estimation', 15th International Conference on Advanced Robotics (ICAR), June 20-23, 2011 (wird in neuem Tab geöffnet) [pdf] [html]

J. Triesch, C. A. Rothkopf, T. H. Weisswange: 'Coordination in Sensory Integration', in Dynamic Coordination in the Brain: From Neurons to Mind, edited by C. von der Malsburg, W. A. Phillips, W. Singer, MIT Press 2010

M. M. Hayhoe, C. A. Rothkopf: 'Vision in the natural world', Wiley Interdisciplinary Reviews: Cognitive Science, Wiley, 2010 (wird in neuem Tab geöffnet) [pdf], [ [html]] image

C. A. Rothkopf, T. H. Weisswange, J. Triesch: 'Computational modeling of multisensory object perception', in 'Multisensory Object Perception in the Primate Brain', Editors: M. J. Naumer & J. Kaiser, New York: Springer, 2010 (wird in neuem Tab geöffnet) [pdf manuscript]

T. H. Weisswange, C. A. Rothkopf, T. Rodemann, J. Triesch: 'Can reinforcement learning explain the development of causal inference in multisensory integration?', IEEE 8th International Conference on Development and Learning, June 5-7, 2009 (wird in neuem Tab geöffnet) [pdf] [html]

C. A. Rothkopf, T. H. Weisswange, J. Triesch: 'Learning independent causes in natural images explains the spacevariant oblique effect', IEEE 8th International Conference on Development and Learning, June 5-7, 2009 (wird in neuem Tab geöffnet) [pdf] [html]

C. A. Rothkopf, D. H. Ballard: 'Image statistics at the point of gaze during human navigation', Visual Neuroscience, special issue on 'Natural Systems Analysis', 26, 81–92, 2009 (wird in neuem Tab geöffnet) [pdf] [html]

C. A. Rothkopf: 'Modular models of task based visually guided behavior', Ph. D. thesis, University of Rochester. Department of Brain and Cognitive Sciences, Department of Computer Science, 2008

C. A. Rothkopf, D. H. Ballard: 'Image statistics at the point of gaze during human navigation', Visual Neuroscience, special issue on 'Natural Systems Analysis', 26, 81–92, 2009 (wird in neuem Tab geöffnet) [pdf], [ [html]] code

J. B. Pelz, C. Rothkopf: 'Oculomotor behavior while navigating natural and man-made environments' in 'Eye movements: A window on mind and brain', Editors: R. van Gompel, M. Fischer, W. Murray, R. Hill. Elsevier Press, 2007

J. F. M. Jehee, C. A. Rothkopf, J. M. Beck, D. H. Ballard: 'Learning receptive fields using predictive feedback', Journal of Physiology Paris, 100, 125-132, 2006 (wird in neuem Tab geöffnet) [pdf] [html]

R. D. Meyer, E. P. Horch, Z. Ninkov, W.F. van Altena, C.A. Rothkopf: 'RYTSI: the Rit-Yale-Tip-Tilt-Speckle-Imager', Publications of the Astronomical Society of the Pacific, 118 , 162-171, 2006 (wird in neuem Tab geöffnet) [pdf] [html]

C. A. Rothkopf, J. B. Pelz: 'Head movement estimation for wearable eye tracker', Proceedings of the Eye Tracking Research & Application Symposium, ETRA 2004, San Antonio, Texas, USA, ACM, 2004 (wird in neuem Tab geöffnet) [pdf] [html]

Additional resources
C. A. Rothkopf. Three levels of description by David Marr slides
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