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in press

  • Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung
    Cheng, S.
    In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze "Mensch". Diskurse des Transhumanismus. Bielefeld: transcript Verlag
  • Learning Cognitive Map Representations for Navigation by Sensorimotor Integration
    Zhao, D., Zhang, Z., Lu, H., Cheng, S., Si, B., & Feng, X.
    IEEE Transactions on Cybernetics

2020

  • Improving sensory representations using episodic memory
    Görler, R., Wiskott, L., & Cheng, S.
    Hippocampus, 30(6), 638–656
  • 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, 101901
  • Perception of the difference between past and present stimulus: A rare orientation illusion may indicate incidental access to prediction error-like signals
    Staadt, R., Philipp, S. T., Cremers, J. L., Kornmeier, J., & Jancke, D.
    PLOS ONE, 15(5), e0232349
  • Separable gain control of ongoing and evoked activity in the visual cortex by serotonergic input
    Azimi, Z., Barzan, R., Spoida, K., Surdin, T., Wollenweber, P., Mark, M. D., et al.
    eLife, 9
  • The Hessian Estimation Evolution Strategy
    Glasmachers, T., & Krause, O.
    In Parallel Problem Solving from Nature (PPSN XVII) Springer
  • Convergence Analysis of the Hessian Estimation Evolution Strategy
    Glasmachers, T., & Krause, O.
    arxiv.org
  • Scene memory and spatial inhibition in visual search: A neural dynamic process model and new experimental evidence
    Grieben, R., Tekülve, J., Zibner, S. K. U., Lins, J., Schneegans, S., & Schöner, G.
    Attention, Perception, & Psychophysics
  • Analyzing Reinforcement Learning Benchmarks with Random Weight Guessing
    Oller, D., Cuccu, G., & Glasmachers, T.
    In International Conference on Autonomous Agents and Multi-Agent Systems
  • Grounding Spatial Language in Perception by Combining Concepts in a Neural Dynamic Architecture
    Sabinasz, D., Richter, M., Lins, J., & Schöner, G.
    In S. Denison, Mack, M., Xu, Y., & Armstrong, B. C. (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 620–626) Cognitive Science Society
  • AI for Social Good: Unlocking the Opportunity for Positive Impact
    Tomašev, N., Cornebise, J., Hutter, F., Picciariello, A., Connelly, B., Belgrave, D. C. M., et al.
    Nature Communications, (2468)

2019

  • Improved graph-based SFA: information preservation complements the slowness principle
    Escalante-B., A. N., & Wiskott, L.
    Machine Learning
  • Hippocampal Reactivation Extends for Several Hours Following Novel Experience
    Giri, B., Miyawaki, H., Mizuseki, K., Cheng, S., & Diba, K.
    The Journal of Neuroscience, 39(5), 866–875
  • Computer mouse tracking reveals motor signatures in a cognitive task of spatial language grounding
    Lins, J., & Schöner, G.
    Attention, Perception, & Psychophysics
  • Moment Vector Encoding of Protein Sequences for Supervised Classification
    Altartouri, H., & Glasmachers, T.
    In Practical Applications of Computational Biology and Bioinformatics, 13th International Conference (pp. 25–35) Springer International Publishing
  • CaMello-XR enables visualization and optogenetic control of Gq/11 signals and receptor trafficking in GPCR-specific domains
    Eickelbeck, D., Karapinar, R., Jack, A., Suess, S. T., Barzan, R., Azimi, Z., et al.
    Communications Biology, 2(1)
  • Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia)
    Azizi, A. H., Pusch, R., Koenen, C., Klatt, S., Bröcker, F., Thiele, S., et al.
    Behavioural Brain Research, 356, 423–434
  • 6DoF Vehicle Pose Estimation Using Segmentation-Based Part Correspondences
    Barowski, T., Szczot, M., & Houben, S.
    In Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 573–580)
  • A Parallel RatSlam C++ Library Implementation
    de Souza Muñoz, M. E., Menezes, M. C., de Freitas, E. P., Cheng, S., de Almeida Neto, A., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R.
    In Communications in Computer and Information Science (pp. 173–183) Springer International Publishing
  • Challenges of Convex Quadratic Bi-objective Benchmark Problems
    Glasmachers, T.
    In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 559–567) ACM
  • Global Convergence of the (1+1) Evolution Strategy
    Glasmachers, T.
    Evolutionary Computation Journal (ECJ)
  • Boosting Reinforcement Learning with Unsupervised Feature Extraction
    Hakenes, S., & Glasmachers, T.
    In Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation (pp. 555–566) Springer International Publishing
  • How do memory modules differentially contribute to familiarity and recollection?
    Hakobyan, O., & Cheng, S.
    Behavioral and Brain Sciences, 42, e288
  • Measuring the Data Efficiency of Deep Learning Methods
    Hlynsson, H., Escalante-B., A., & Wiskott, L.
    In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods SCITEPRESS - Science and Technology Publications
  • Learning Gradient-Based ICA by Neurally Estimating Mutual Information
    Hlynsson, H. D. ′ið, & Wiskott, L.
    In C. Benzmüller & Stuckenschmidt, H. (Eds.), KI 2019: Advances in Artificial Intelligence (pp. 182–187) Cham: Springer International Publishing
  • Park marking-based vehicle self-localization with a fisheye topview system
    Houben, S., Neuhausen, M., Michael, M., Kesten, R., Mickler, F., & Schuller, F.
    Journal of Real-Time Image Processing, 16(2), 289–304
  • A process account of the UnControlled Manifold uncontrolled manifold structure of joint space variance in pointing movements
    Martin, V., Reimann, H., & Schöner, G.
    Biological Cybernetics
  • Fusing Shape-from-Silhouette and the Sparsity Driven Detector for Camera-Based 3D Multi-Object Localization with Occlusions
    Michael, M., Horn, D., & Houben, S.
    In Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 1417–1424)
  • Vehicle Shape and Color Classification Using Convolutional NeuralNetwork
    Nafzi, M., Brauckmann, M., & Glasmachers, T.
    arxiv.org
  • Dual SVM Training on a Budget
    Qaadan, S., Schüler, M., & Glasmachers, T.
    In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods SCITEPRESS - Science and Technology Publications
  • Modeling Macroscopic Material Behavior With Machine Learning Algorithms Trained by Micromechanical Simulations
    Reimann, D., Nidadavolu, K., ul Hassan, H., Vajragupta, N., Glasmachers, T., Junker, P., & Hartmaier, A.
    Frontiers in Materials, 6, 181
  • SpikeDeeptector: A deep-learning based method for detection of neural spiking activity
    Saif-ur-Rehman, M., Lienkämper, R., Parpaley, Y., Wellmer, J., Liu, C., Lee, B., et al.
    Journal of Neural Engineering
  • The Dynamics of Neural Populations Capture the Laws of the Mind
    Schöner, G.
    Topics in Cognitive Science, 1–15
  • Generation of Natural Traffic Sign Images Using Domain Translation with Cycle-Consistent Generative Adversarial Networks
    Spata, D., Horn, D., & Houben, S.
    In Proceedings of the IEEE Intelligent Vehicles Symposium (IV) (pp. 622–628)
  • Autonomous Sequence Generation for a Neural Dynamic Robot: Scene Perception, Serial Order, and Object-Oriented Movement
    Tekülve, J., Fois, A., Sandamirskaya, Y., & Schöner, G.
    Frontiers in Neurorobotics, 13, 95
  • Neural dynamic concepts for intentional systems
    Tekülve, J., & Schöner, G.
    In 41th Annual Conference of the Cognitive Science Society (CogSci 2019)
  • Autonomously learning beliefs is facilitated by a neural dynamic network driving an intentional agent
    Tekülve, J., & Schöner, G.
    In Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2019 Joint IEEE International Conference on (pp. 143–150) IEEE
  • Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening
    Schüler, M., Hlynsson, H. D. ′ið, & Wiskott, L.
    In W. S. Lee & Suzuki, T. (Eds.), Proceedings of The Eleventh Asian Conference on Machine Learning (Vol. 101, pp. 316–331) Nagoya, Japan: PMLR