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  • Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung
    Cheng, S.
    In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze "Mensch". Diskurse des Transhumanismus. Bielefeld: transcript Verlag
  • Bridging the gap between single receptor type activity and whole-brain dynamics
    Jancke, D., Herlitze, S., Kringelbach, M. L., & Deco, G.
    The FEBS Journal

2021

  • A multistage retrieval account of associative recognition ROC curves
    Hakobyan, O., & Cheng, S.
    Learning and Memory, 28(11), 400–404
  • Improved Protein Function Prediction by Combining Clustering with Ensemble Classification
    Altartouri, H., & Glasmachers, T.
    Journal of Advances in Information Technology (JAIT)
  • Emergence of complex dynamics of choice due to repeated exposures to extinction learning
    Donoso, J. R., Packheiser, J., Pusch, R., Lederer, Z., Walther, T., Uengoer, M., et al.
    Animal Cognition, 24(6), 1279–1297
  • Recognition Receiver Operating Characteristic Curves: The Complex Influence of Input Statistics, Memory, and Decision-making
    Hakobyan, O., & Cheng, S.
    Journal of Cognitive Neuroscience, 33(6), 1032–1055
  • Darks and Lights, the `Yin–Yang′ of Vision Depends on Luminance
    Jancke, D.
    Trends in Neurosciences, 44(5), 339–341
  • Basal ganglia and cortical control of thalamic rebound spikes
    Nejad, M. M., Rotter, S., & Schmidt, R.
    European Journal of Neuroscience, 54(1), 4295–4313
  • Self-referential false associations: A self-enhanced constructive effect for verbal but not pictorial stimuli
    Wang, J., Otgaar, H., Howe, M. L., & Cheng, S.
    Quarterly Journal of Experimental Psychology, 74(9), 1512–1524
  • How do neural processes give rise to cognition? Simultaneously predicting brain and behavior with a dynamic model of visual working memory.
    Buss, A. T., Magnotta, V. A., Penny, W., Schöner, G., Huppert, T. J., & Spencer, J. P.
    Psychological Review, 128(2), 362–395
  • Trial-by-trial dynamics of reward prediction error-associated signals during extinction learning and renewal
    Packheiser, J., Donoso, J. R., Cheng, S., Güntürkün, O., & Pusch, R.
    Progress in Neurobiology, 197, 101901
  • Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach
    Walther, T., Diekmann, N., Vijayabaskaran, S., Donoso, J. R., Manahan-Vaughan, D., Wiskott, L., & Cheng, S.
    Scientific Reports, 11(1)
  • Dynamic Door Modeling for Monocular 3D Vehicle Detection
    Barowski, T., Brehme, A., Szczot, M., & Houben, S.
    In Proceedings of the IEEE Intelligent Vehicles Symposium (IV) (pp. 1359–1365)
  • Application of Reinforcement Learning to a Mining System
    Fidencio, A., Naro, D., & Glasmachers, T.
    In 19th IEEE World Symposium on Applied Machine Intelligence and Informatics (SAMI′2021)
  • Convergence Analysis of the Hessian Estimation Evolution Strategy
    Glasmachers, T., & Krause, O.
    Evolutionary Computation Journal (ECJ)
  • A neural dynamic process model of combined bottom-up and top-down guidance in triple conjunction visual search
    Grieben, R., & Schöner, G.
    In T. Fitch, Lamm, C., Leder, H., & Teßmar-Raible, K. (Eds.), Proceedings of the 43nd Annual Conference of the Cognitive Science Society Cognitive Science Society
  • Automated Selection of High-Quality Synthetic Images for Data-Driven Machine Learning: A Study on Traffic Signs
    Horn, D., Janssen, L., & Houben, S.
    In Proceedings of the IEEE Intelligent Vehicles Symposium (IV) (pp. 832–837)
  • Fully Automated, Realistic License Plate Substitution in Real-Life Images
    Kacmaz, U., Melchior, J., Horn, D., Witte, A., Schoenen, S., & Houben, S.
    In Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 2972–2979)
  • Exploring Slow Feature Analysis for Extracting Generative Latent Factors
    Menne, M., Schüler, M., & Wiskott, L.
    In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods SCITEPRESS - Science and Technology Publications
  • Non-local Optimization: Imposing Structure on Optimization Problems by Relaxation
    Müller, N., & Glasmachers, T.
    In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA′21) Association for Computing Machinery
  • Neuronal Sequences during Theta Rely on Behavior-Dependent Spatial Maps
    Parra-Barrero, E., Diba, K., & Cheng, S.
    eLife, 10, e70296
  • A Neural Dynamic Model of the Perceptual Grounding of Spatial and Movement Relations
    Richter, M., Lins, J., & Schöner, G.
    Cognitive Science, 45(10), e13045
  • Pay-as-you-go Population of an Automotive Signal Knowledge Graph
    Svetashova, Y., Lars Heling,, Stefan Schmid,, & Maribel Acosta,
    In The Semantic Web - 18th International Conference, ESWC 2021, Virtual Event, June 6-10, 2021, Proceedings (Vol. 12731, pp. 717–735) Springer
  • Predicting Instance Type Assertions in Knowledge Graphs Using Stochastic Neural Networks
    Weller, T., & Acosta, M.
    In 30th ACM International Conference on Information and Knowledge Management (CIKM) ACM