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2018

  • TMS-induced neuronal plasticity enables targeted remodeling of visual cortical maps
    Kozyrev, V., Staadt, R., Eysel, U. T., & Jancke, D.
    Proceedings of the National Academy of Sciences, 115(25), 6476–6481
    link
  • The Interaction between Semantic Representation and Episodic Memory
    Fang, J., Rüther, N., Bellebaum, C., Wiskott, L., & Cheng, S.
    Neural Computation, 30(2), 293–332
  • Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success Rule
    Akimoto, Y., Auger, A., & Glasmachers, T.
    In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) ACM
    link 1802.03209.pdf
  • 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 (accepted)
  • The Reduction of Adult Neurogenesis in Depression Impairs the Retrieval of New as Well as Remote Episodic Memory.
    Fang, J., Demic, S., & Cheng, S.
    PLOS ONE, accepted
  • Sequences of discrete attentional shifts emerge from a neural dynamic architecture for conjunctive visual search that operates in continuous time
    Grieben, R., Tekülve, J., Zibner, S. K. U., Schneegans, S., & Schöner, G.
    In Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 1–6)
    preprint
  • Anticipatory coarticulation in non-speeded arm movements can be motor-equivalent, carry-over coarticulation always is
    Hansen, E., Grimme, B., Reimann, H., & Schöner, G.
    Experimental Brain Research
    reprint
  • Automatisierte Videoanalyse
    Horn, D., Ibisch, A., & Tschentscher, M.
    In C. Moritz & Corsten, M. (Eds.), Handbuch Qualitative Videoanalyse (pp. 445–456) Springer VS Verlag
  • A Neural Dynamic Architecture That Autonomously Builds Mental Models
    Kounatidou, P., Richter, M., & Schöner, G.
    In Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 1–6)
    preprint
  • Challenges in High-dimensional Controller Design with Evolution Strategies
    Müller, N., & Glasmachers, T.
    In Parallel Problem Solving from Nature (PPSN XVI) Springer
    arXiv software
  • Organic Face Graph Classification
    Nilkens, A.
    In S. Tomforde & Sick, B. (Eds.), Organic Computing: Doctoral Dissertation Colloquium 2017 (Vol. 11, pp. 79–92) kassel university press GmbH
  • Unsupervised Acquisition of Human Body Models
    Walther, T., & Würtz, R. P.
    Cognitive Systems Research, 47, 68–84
    Article Additional material
  • Slowness as a Proxy for Temporal Predictability: An Empirical Comparison
    Weghenkel, B., & Wiskott, L.
    Neural Computation, 30(5), 1151–1179
  • Doing without metarepresentation: Scenario construction explains the epistemic generativity and privileged status of episodic memory
    Werning, M., & Cheng, S.
    Behavioral and Brain Sciences, 41
  • Interactive Learning Without Ground Truth
    Würtz, R. P., Tomforde, S., Calma, A., Kottke, D., & Sick, B.
    In S. Tomforde & Sick, B. (Eds.), Organic Computing: Doctoral Dissertation Colloquium 2017 (Vol. 11, p. II.1–II.4) kassel university press GmbH

2017

  • Unsupervised Acquisition of Human Body Models using Principles of Organic Computing
    Walther, T., & Würtz, R. P.
    ArXiv e-prints
  • A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating
    Knips, G., Zibner, S. K. U., Reimann, H., & Schöner, G.
    Frontiers in Neurorobotics, 11(March), 9:1–14
    reprint
  • Gaussian-binary restricted Boltzmann machines for modeling natural image statistics
    Melchior, J., Wang, N., & Wiskott, L.
    PLOS ONE, 12(2), 1–24
  • Generating sequences in recurrent neural networks for storing and retrieving episodic memories
    Bayati, M., Melchior, J., Wiskott, L., & Cheng, S.
    In Proc. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2
  • Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung
    Cheng, S.
    In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze . Diskurse des Transhumanismus. (p. invited contribution) Bielefeld: transcript Verlag
  • Consolidation of Episodic Memory: An Epiphenomenon of Semantic Learning
    Cheng, S.
    In N. Axmacher & Rasch, B. (Eds.), Cognitive Neuroscience of Memory Consolidation (pp. 57–72) Cham, Switzerland: Springer International Publishing
  • Experience-Dependency of Reliance on Local Visual and Idiothetic Cues for Spatial Representations Created in the Absence of Distal Information
    Draht, F., Zhang, S., Rayan, A., Schönfeld, F., Wiskott, L., & Manahan-Vaughan, D.
    Frontiers in Behavioral Neuroscience, 11(92)
  • Extensions of Hierarchical Slow Feature Analysis for Efficient Classification and Regression on High-Dimensional Data
    Escalante-B., A. N.
    Doctoral thesis, Ruhr University Bochum, Faculty of Electrical Engineering and Information Technology
    PhD Thesis
  • A Fast Incremental BSP Tree Archive for Non-dominated Points
    Glasmachers, T.
    In Evolutionary Multi-Criterion Optimization (EMO) Springer
    pdf code
  • Limits of End-to-End Learning
    Glasmachers, T.
    In Proceedings of the 9th Asian Conference on Machine Learning (ACML)
    pdf code proceedings
  • Global Convergence of the (1+1) Evolution Strategy
    Glasmachers, T.
    arxiv.org
    pdf arXiv.org
  • Cue Integration by Similarity Rank List Coding — Application to Invariant Object Recognition
    Grieben, R., & Würtz, R. P.
    In Proceedings of IEEE International Workshops on Foundations and Applications of Self* Systems (pp. 132–137)
    pdf
  • Texture attribute synthesis and transfer using feed-forward CNNs
    Irmer, T., Glasmachers, T., & Maji, S.
    In Winter Conference on Applications of Computer Vision (WACV) IEEE
    pdf
  • Catching the voltage gradient—asymmetric boost of cortical spread generates motion signals across visual cortex: a brief review with special thanks to Amiram Grinvald
    Jancke, D.
    Neurophoton., 4(3), 031206
  • Intrinsically Motivated Acquisition of Modular Slow Features for Humanoids in Continuous and Non-Stationary Environments
    Kompella, V. R., & Wiskott, L.
    arXiv preprint arXiv:1701.04663
  • Qualitative and Quantitative Assessment of Step Size Adaptation Rules
    Krause, O., Glasmachers, T., & Igel, C.
    In Conference on Foundations of Genetic Algorithms (FOGA) ACM
    pdf
  • Mouse Tracking Shows Attraction to Alternative Targets While Grounding Spatial Relations
    Lins, J., & Schöner, G.
    In Proceedings of the 39th Annual Conference of the Cognitive Science Society Austin, TX: Cognitive Science Society
  • A Neural-Dynamic Architecture for Concurrent Estimation of Object Pose and Identity
    Lomp, O., Faubel, C., & Schöner, G.
    Frontiers in Neurorobotics, 11(April), 23
    reprint
  • From grid cells to place cells with realistic field sizes
    Neher, T., Azizi, A. H., & Cheng, S.
    PLoS ONE, 12(7), e0181618
  • A multi-joint model of quiet , upright stance accounts for the “uncontrolled manifold”-structure of joint variance
    Reimann, H., & Schöner, G.
    Biological Cybernetics, in press
    preprint
  • A neural dynamic model generates descriptions of object-oriented actions
    Richter, M., Lins, J., & Schöner, G.
    Topics in Cognitive Science, 9(1), 35–47
    A neural dynamic model generates descriptions of object-oriented actions (PDF)
  • Reaching for objects : a neural process account in a developmental perspective
    Schöner, G., Tekülve, J., & Zibner, S.
    In D. Corbetta & Santello, M. (Eds.), The selection and production of goal-directed behaviors: Neural correlates, development, learning, and modeling of reach-to-grasp movements Taylor & Francis
    preprint
  • Dynamic Neural Fields with Intrinsic Plasticity
    Strub, C., Schöner, G., Wörgötter, F., & Sandamirskaya, Y.
    Frontiers in Computational Neuroscience, 11(August), 74
    reprint
  • A simulated car-park environment for the evaluation of video-based on-site parking guidance systems
    Tschentscher, M., Pruß, B., & Horn, D.
    In Proceedings of the IEEE Intelligent Vehicles Symposium (IV) (pp. 1571–1576)
    Paper
  • Graph-based predictable feature analysis
    Weghenkel, B., Fischer, A., & Wiskott, L.
    Machine Learning, 1–22
    preprint
  • Taxonomy and Unity of Memory
    Werning, M., & Cheng, S.
    In S. Bernecker & Michaelian, K. (Eds.), The Routledge Handbook of Philosophy of Memory (p. forthcoming) London: Routledge
  • No need for meta-representation: How scenario construction explains the epistemic generativity and privileged epistemic status of episodic memory
    Werning, M., & Cheng, S.
    Behavioral and Brain Sciences, in press

2016

  • Topological Schemas of Cognitive Maps and Spatial Learning
    Babichev, A., Cheng, S., & Dabaghian, Y. A.
    Frontiers in Computational Neuroscience, 10, 18
  • What is episodic memory if it is a natural kind?
    Cheng, S., & Werning, M.
    Synthese, 193(5), 1345–1385
  • Dissociating memory traces and scenario construction in mental time travel
    Cheng, S., Werning, M., & Suddendorf, T.
    Neuroscience & Biobehavioral Reviews, 60, 82–89
  • Fast model selection by limiting SVM training times
    Demircioğlu, A., Horn, D., Glasmachers, T., Bischl, B., & Weihs, C.
    arxiv.org
    pdf arXiv.org
  • A Unified View on Multi-class Support Vector Classification
    Doğan, Ü., Glasmachers, T., & Igel, C.
    Journal of Machine Learning Research, 17(45), 1–32
    pdf jmlr.org
  • Theoretical analysis of the optimal free responses of graph-based SFA for the design of training graphs.
    Escalante-B., A. N., & Wiskott, L.
    Journal of Machine Learning Research, 17(157), 1–36
    Theoretical analysis of the optimal free responses of graph-based SFA for the design of training graphs
  • Improved graph-based SFA: Information preservation complements the slowness principle
    Escalante-B., A. N., & Wiskott, L.
    e-print arXiv:1601.03945
    Improved graph-based SFA: Information preservation complements the slowness principle
  • Phase based forgery detection of JPEG anti forensics
    Fahmy, G., & Wurtz, R.
    In Signal Processing and Information Technology (ISSPIT), 2016 IEEE International Symposium on (pp. 144–149) IEEE
  • Finite Sum Acceleration vs. Adaptive Learning Rates for the Training of Kernel Machines on a Budget
    Glasmachers, T.
    In NIPS workshop on Optimization for Machine Learning
    pdf code
  • Small Stochastic Average Gradient Steps
    Glasmachers, T.
    In NIPS workshop on Optimizing the Optimizers
    pdf
  • Nonlinear dynamics in the perceptual grouping of connected surfaces
    Hock, H. S., & Schöner, G.
    Vision Research, 126, 80–96
    reprint
  • A Comparative Study on Large Scale Kernelized Support Vector Machines
    Horn, D., Demircioğlu, A., Bischl, B., Glasmachers, T., & Weihs, C.
    Advances in Data Analysis and Classification (ADAC), 1–17
    springer.com
  • Unbounded Population MO-CMA-ES for the Bi-Objective BBOB Test Suite
    Krause, O., Glasmachers, T., Hansen, N., & Igel, C.
    In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)
    pdf
  • Multi-objective Optimization with Unbounded Solution Sets
    Krause, O., Glasmachers, T., & Igel, C.
    In NIPS workshop on Bayesian Optimization
    pdf
  • Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar
    Lomp, O., Richter, M., Zibner, S. K. U., & Schöner, G.
    Frontiers in Neurorobotics, 10(November), 14
    reprint
  • Anytime Bi-Objective Optimization with a Hybrid Multi-Objective CMA-ES (HMO-CMA-ES)
    Loshchilov, I., & Glasmachers, T.
    In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)
    pdf
  • How to Center Deep Boltzmann Machines
    Melchior, J., Fischer, A., & Wiskott, L.
    Journal of Machine Learning Research, 17(99), 1–61
  • Fast Change Detection for Camera-based Surveillance Systems
    Michael, M., Feist, C., Schuller, F., & Tschentscher, M.
    In Proceedings of the IEEE International Conference on Intelligent Transportation Systems (Vol. 19, pp. 1–8)
    Fast Change Detection for Camera-based Surveillance Systems
  • Coordination of muscle torques stabilizes upright standing posture: an UCM analysis
    Park, E., Reimann, H., & Schöner, G.
    Experimental Brain Research, 234(6), 1757–1767
    preprint
  • Separating Timing, Movement Conditions and Individual Differences in the Analysis of Human Movement
    Raket, L. L., Grimme, B., Schöner, G., Igel, C., & Markussen, B.
    PLoS Computational Biology, 12(9), 1–27
    reprint
  • Temporal asymmetry in dark-bright processing initiates propagating activity across primary visual cortex
    Rekauzke, S., Nortmann, N., Staadt, R., Hock, H. S., Schöner, G., & Jancke, D.
    J Neurosci, 36(6), 1902–1913
    pdf
  • A neural dynamic model parses object-oriented actions
    Richter, M., Lins, J., & Schöner, G.
    In A. Papafragou, Grodner, D., Mirman, D., & Trueswell, J. C. (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp. 1931–1936) Austin, TX: Cognitive Science Society
    pdf
  • A computational model of spatial encoding in the hippocampus
    Schönfeld, F.
    Doctoral thesis, Ruhr-Universität Bochum
  • Melanopsin variants as intrinsic optogenetic On and Off switches for transient versus sustained activation of G protein pathways
    Spoida, K., Eickelbeck, D., Karapinar, R., Eckhardt, T., Mark, M. D., Jancke, D., et al.
    Curr Biol., 26(9), 1206–1212
  • A neural process model of learning to sequentially organize and activate pre-reaches
    Tekülve, J., Zibner, S. K. U., & Schöner, G.
    In Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2016 Joint IEEE International Conferences on
    A neural process model of learning to sequentially organize and activate pre-reaches
  • "Self-Improving System Integration" – Preface for the SISSY′16 Workshop
    Tomforde, S., Rudolph, S., Bellman, K., & Würtz, R. P.
    In Proc. ICAC (p. 275)
    pdf
  • An Organic Computing Perspective on Self-Improving System Interweaving at Runtime
    Tomforde, S., Rudolph, S., Bellman, K., & Würtz, R. P.
    In Proc. ICAC (pp. 276–284)
    pdf
  • Supervised Classification
    Weihs, C., & Glasmachers, T.
    In C. Weihs, Jannach, D., Vatolkin, I., & Rudolph, G. (Eds.), Music Data Analysis: Foundations and Applications

2015

  • Phase based detection of JPEG counter forensics
    Fahmy, G., Alqallaf, A., & Wurtz, R.
    In 2015 IEEE International Conference on Electronics, Circuits, and Systems (ICECS) (pp. 37–40)
    pdf
  • Memory Storage Fidelity in the Hippocampal Circuit: The Role of Subregions and Input Statistics
    Neher, T., Cheng, S., & Wiskott, L.
    PLOS Computational Biology, 11(5), 1–25
  • Self-organization of synchronous activity propagation in neuronal networks driven by local excitation
    Bayati, M., Valizadeh, A., Abbassian, A., & Cheng, S.
    Frontiers in Computational Neuroscience, 9, 69