Veröffentlichungen

D. Endres, M. Alam, & D. Şotropa, editors. Graph-Based Representation and Reasoning, volume 24 of International Conference on Conceptual Structures. Springer, 2018.

DOI: 10.1007/978-3-030-23182-8

 P. Chapman, D. Endres & N. Pernelle, editors. Graph-Based Representation and Reasoning, volume 23 of International Conference on Conceptual Structures. Springer, 2018.

DOI: 10.1007/978-3-319-91379-7 BibTeX

A. Schütz, C., A. Schubö, D. Endres & H. Lachnit, editors.  Abstracts of the 60th conference of experimental psychologists. Pabst Science Publishers, 2018.

DOI: 10.23668/psycharchives.913

Raghuveer, D. & Endres, D. (2023).
Active Inference and Psychology of Expectations: A Study of Formalizing ViolEx. In: , et al. Active Inference. IWAI 2022. Communications in Computer and Information Science, vol 1721. Springer, Cham.

DOI: 10.1007/978-3-031-28719-0_17 BibTeX

Mukovskiy, A., Taubert, N., Endres, D., Vassallo, C., Naveau, M., Stasse, O., Souères, P. & Giese; M. A. (2017)
Modeling of coordinated human body motion by learning of structured dynamic representations
Geometric and Numerical Foundations of Movements, Springer, 2017 , 117 , 237-268

DOI: 10.1007/978-3-319-51547-2 BibTeX

Endres, D., Chiovetto, E. & Giese, M. (2015)
Bayesian approaches for learning of primitive-based compact representations of complex human activities
Dance notation and robot motion, Springer, 2015 , 117-137

DOI: 10.1007/978-3-319-25739-6 6 BibTeX PDF

Meibodi, N., Abbasi, H., Schubö, A. et al. (2024)
Distracted by Previous Experience: Integrating Selection History, Current Task Demands and Saliency in an Algorithmic Model.
Comput Brain Behav

DOI: 10.1007/s42113-024-00197-6 BibTex PDF

Leh, A., .Endres, D., Hegele, M. (2023)
A primitive-based representation of dance: modulations by experience and perceptual validity
Journal of Neurophysiology, 2023 130:5, 1214-1225.

DOI: 10.1152/jn.00161.2023 BibTex

Herzog, P., Feldmann, M., Kube, T., Langs, G., Gärtner, T., Rauh, E., Doerr, R., Hillert, A., Voderholzer, U., Rief, W., Endres, D. & Brakemeier, E.-L. (2022)
Inpatient psychotherapy for depression in a large routine clinical care sample: A Bayesian approach to examining clinical outcomes and predictors of change
Journal of Affective Disorders, 305:133-143.

DOI: 10.1016/j.jad.2022.02.057 BibTex

Stroth, S., Niehaus, H., Wolff, N., Poustka, L., Roessner, V., Kamp-Becker, I. & Endres, D. (2022)
Subdimensions of social-communication behavior in autism—A replication study
Psychological review.

DOI: 10.1002/jcv2.12077 BibTex

Binz, M., Gershman, S. J., Schulz, E. & Endres, D. (2022)
Heuristics from bounded meta-learned inference.
Psychological review, 129(5), 1042–1077. 

DOI: 10.1037/rev0000330 BibTex

Panitz, C., Endres, D., Buchholz, M., Khosrowtaj, Z., Sperl, M. F. J., Mueller, E. M., Schubö, A., Schütz, A. C., Teige-Mocigemba, S. & Pinquart, M. (2021)
A Revised Framework for the Investigation of Expectation Update Versus Maintenance in the Context of Expectation Violations: The ViolEx 2.0 Model
Frontiers in Psychology, 12.

DOI: 10.3389/fpsyg.2021.726432 BibTex

Schubert, M. & Endres, D. (2021)
More Plausible Models of Body Ownership Could Benefit Virtual Reality Applications
Computers, 10(9).

DOI: 10.3390/computers10090108 BibTex

Pinquart, M., Endres, D., Teige-Mocigemba, S., Panitz, C. & Schütz, A. C. (2021)
Why expectations do or do not change after expectation violation: A comparison of seven models.
Consciousness and Cognition, 89:103086.

DOI: 10.1016/j.concog.2021.103086 BibTex

Kern, P., Assaneo, M., Endres, D., Poeppel, D. & Rimmele, J. (2021)
Preferred auditory temporal processing regimes and auditorymotor synchronization.
Psychonomic Bulletin & Review, 28(6):1860-1873

DOI: 10.3758/s13423-021-01933-w BibTex

Knopp, B., Velychko, D., Dreibrodt, J. & Endres, D. (2019)
Predicting perceived naturalness of human animations based on generative movement primitive models.
ACM Trans. Appl. Percept., 16(3)

DOI: 10.1145/3355401 BibTex

Stolz, C.; Endres, D. & Müller, E. (2019)
Threat-Conditioned contexts modulate the late positive potential to faces — a mobile EEG/virtual reality study.
Psychophysiology, 56(4):e13308

DOI: 10.1111/psyp.13308 BibTex

Velychko, D., Knopp, B. & Endres, D. (2018)
Making the Coupled Gaussian Process Dynamical Model Modular and Scalable with Variational Approximations.
Entropy, 2018, 20

DOI: 10.3390/e20100724 BibTeX PDF

Junker, M., Endres, D., Sun, Z., Dicke, P., Giese, M. & Thier, P. (2018)
Learning from the past: A reverberation of past errors in the cerebellar climbing fiber signal.
PLoS Biology, 2018, 16, e2004344

DOI: 10.1371/journal.pbio.2004344 BibTeX PDF

Chiovetto, E., Curio, C., Endres*, D. & Giese*, M. (2018)
Perceptual integration of kinematic components in the recognition of emotional facial expressions.
Journal of Vision, 2018, 18, 13

DOI: 10.1167/18.4.13 BibTeX PDF

Quaglio, P., Yegenoglu, A., Torre, E., Endres*, D. & Grün*, S. (2017)
Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.
Frontiers in Computational Neuroscience, 2017, 11 , 41

DOI: 10.3389/fncom.2017.00041 BibTeX PDF

Clever, D., Harant, M., Mombaur, K., Naveau, M., Stasse, O. & Endres, D. (2017)
COCoMoPL: A Novel Approach for Humanoid Walking Generation Combining Optimal Control, Movement Primitives and Learning and its Transfer to the Real Robot HRP-2.
IEEE Robotics and Automation Letters, 2017 , 2 , 977-984

DOI: 10.1109/LRA.2017.2657000 BibTeX PDF

Hechler, T., Endres, D. & Thorwart, A. (2016)
Why Harmless Sensations Might Hurt in Individuals with Chronic Pain: About Heightened Prediction and Perception of Pain in the Mind.
Frontiers in Psychology, 2016 , 7, 1638

DOI: 10.3389/fpsyg.2016.01638 BibTeX PDF

Clever, D., Harant, M., Koch, K. H., Mombaur, K. & Endres, D. (2016)
A novel approach for the generation of complex humanoid walking sequences based on a combination of optimal control and learning of movement primitives.
Robotics and Autonomous Systems, 2016 , 83, 287-298

DOI: 10.1016/j.robot.2016.06.001 BibTeX

Doolittle, E., Gingras, B., Endres, D. & Fitch, W. (2014)
Overtone-based pitch selection in hermit thrush song: Unexpected convergence with scale construction in human music.
Proceedings of the National Academy of Sciences of the United States of America, 2014 , 111 , 16616-16621

DOI: 10.1073/pnas.1406023111 BibTeX PDF

Endres, D., Chiovetto, E. & Giese, M. (2013)
Model selection for the extraction of movement primitives.
Frontiers in Computational Neuroscience, 2013, 7, 185

DOI: 10.3389/fncom.2013.00185 BibTeX PDF

Endres, D., Meirovitch, Y., Flash, T. & Giese, M. (2013)
Segmenting sign language into motor primitives with Bayesian binning.
Frontiers in Computational Neuroscience, 2013, 7, 68

DOI: 10.3389/fncom.2013.00185 BibTeX PDF

Endres, D., Christensen, A.; Omlor, L. & Giese, M. A. (2011)
Emulating human observers with Bayesian binning: segmentation of action streams.
ACM Transactions on Applied Perception (TAP), 2011, 8, 16:1-12

DOI: 10.1145/2010325.2010326 BibTeX PDF

Endres, D., Földiák, P. & Priss, U. (2010)
An Application of Formal Concept Analysis to Semantic Neural Decoding.
Annals of Mathematics and Artificial Intelligence, 2010 , 57 , 233-248

DOI: 10.1007/s10472-010-9196-8 BibTeX

Endres, D., Schindelin, J., Földiák, P. & Oram, M. (2010)
Modelling spike trains and determining latencies with Bayesian binning.
Journal of Physiology (Paris), 2010, 104

DOI: 10.1016/j.jphysparis.2009.11.015 BibTeX

Endres, D. & Oram, M. (2010)
Feature extraction from spike trains with Bayesian binning: 'latency is where the signal starts'.
Journal of Computational Neuroscience, 2010 , 29 , 149-169

DOI: 10.1007/s10827-009-0157-3 BibTeX PDF

Földiák, P. & Endres, D. (2008)
Sparse coding.
Scholarpedia, 2008, 3, 2984

DOI: 10.4249/scholarpedia.2984 BibTeX PDF

Endres, D. & Földiák, P. (2008)
Exact Bayesian Bin Classification: a fast alternative to Bayesian Classification and its application to neural response analysis.
Journal of Computational Neuroscience, 2008, 24, 24-35

DOI: 10.1007/s10827-007-0039-5 BibTeX PDF

Endres, D. & Földiák, P. (2005)
Bayesian bin distribution inference and mutual information.
IEEE Transactions on Information Theory, 2005, 51, 3766-3779

DOI: 10.1109/TIT.2005.856954 BibTeX PDF

Endres, D. & Schindelin, J. (2002)
A new metric for probability distributions.
IEEE Transactions on Information Theory, 2002, 49, 1858-1860

DOI: 10.1109/TIT.2003.813506 BibTeX PDF

Endres, D. & Riegler, P. (1999)
Learning dynamics on different timescales.
Journal of Physics A: Mathematical and General, 1999, 32, 8655-8663

DOI: 10.1088/0305-4470/32/49/306 BibTeX

Langsdorf, L., Goehringer, F., Schween, R., Schenk, T. & Hegele, M.
Additional cognitive load decreases performance but not adaptation to a visuomotor transformation.
Acta Psychologica, 226:103586.

DOI: 10.1016/j.actpsy.2022.103586 BibTex

Weilnhammer, V., Fritsch, M., Chikermane, M., Eckert, A.-L., Kanthak, K., Stuke, H., Kaminski, J. & Sterzer, P.
An active role of inferior frontal cortex in conscious experience.
Current Biology, 31(13):2868- 2880.e8.

DOI: 10.1016/j.cub.2021.04.043 BibTex

Forano M*, Schween R*, Taylor JA, Hegele M & Franklin DW.
Direct and indirect cues can enable dual-adaptation, but through different learning processes.
J Neurophysiol: /in press/
*equal contribution

DOI: 10.1152/jn.00166.2021 DOI (bioRxiv): 10.1101/2021.04.09.439164

Langsdorf L, Maresch J, Hegele M, McDougle SD* & Schween R*.
Prolonged response time helps eliminate residual errors in visuomotor adaptation.
Psychonomic Bulletin & Review 28: 834-844, 2021
*equal contribution

DOI: 10.3758/s13423-020-01865-x PDF

Schween, R., McDougle, S. D., Hegele, M. & Taylor, J. A.
Assessing explicit strategies in force field adaptation.
Journal of Neurophysiology, 123(4):1552–1565

DOI: 10.1152/jn.00427.2019 BibTex

Weilnhammer, V., Röd, L., Eckert, A.-L., Stuke, H., Heinz, A. & Sterzer, P.
Psychotic Experiences in Schizophrenia and Sensitivity to Sensory Evidence.
Schizophrenia Bulletin, 46(4):927–936

DOI: 10.1093/schbul/sbaa003 BibTex

Schween, R., Langsdorf, L., Taylor, J. A. & Hegele, M.
How different effectors and action effects modulate the formation of separate motor memories.
Scientific Reports, 9(1):17040

DOI: 10.1038/s41598-019-53543-1 BibTex

Robadey, J., Staudenmann, D., Schween, R., Gehring, D., Gollhofer, A. & Taube, W.
Lower between-limb asymmetry during running on treadmill compared to overground in subjects with laterally pronounced knee osteoarthritis.
PLOS ONE, 13(10):1–12

DOI: 10.1371/journal.pone.0205191 BibTeX

Schween, R., Taylor, J. A. & Hegele, M.
Plan-based generalization shapes local implicit adaptation to opposing visuomotor transformations.
Journal of Neurophysiology, 120(6):2775-2787

DOI: 10.1152/jn.00451.2018 BibTeX

Pabst, K., Zittrell, F., Endres, D. & Homberg, U.
A Model for Optic Flow Integration in Locust Central-Complex Neurons Tuned to Head Direction.
Proceedings of the Annual Meeting of the Cognitive Science Society.

DOI: 10.17192/fdr/90 BibTeX

Niehaus, H., Stroth, S., Kamp-Becker, I., & Endres, D.
Modeling aberrant volatility estimates in Autism Spectrum Disorder.
Proceedings of the Annual Meeting of the Cognitive Science Society.

DOI: 10.17192/fdr/87 BibTeX

Meibodi, N., Schubö, A. & Endres, D.
Sensorimotor processes are not a source of much noise: sensorimotor and decision components of reaction times.
Proceedings of the Annual Meeting of the Cognitive Science Society.

DOI: 10.17192/fdr/88 BibTeX

Augustat, N., Chuang, L.-C., Panitz, C., Stolz, C., Müller*, E. M. & Endres*, D.
Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach.
Proceedings of the Annual Meeting of the Cognitive Science Society.
*equal contribution

DOI: 10.17192/fdr/89 BibTeX

Meibodi, N., Abbasi, H., Schubö, A. & Endres, D. M.
A model of selection history in visual attention.
Proceedings of the Annual Meeting of the Cognitive Science Society, volume 43.

PDF BibTeX

Schubert, M. & Endres, D.
The Bayesian Causal Inference of Body Ownership Model: Use in VR and Plausible Parameter Choices.
2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), pages 67-70.

DOI: 10.1109/VRW52623.2021.00019 BibTeX

Knopp, B., Velychko, D., Dreibrodt, J., Schütz, A. C. & Endres, D.
Evaluating Perceptual Predictions Based on Movement Primitive Models in VR- and Online-Experiments.
ACM Symposium on Applied Perception 2020, SAP '20, New York, NY, USA. Association for Computing Machinery.

DOI: 10.1145/3385955.3407940 BibTeX

Serr, A., Schubert, M., & Endres, D.
Mathematical Similarity Models: Do We Need Incomparability to Be Precise?
Graph-Based Representation and Reasoning, pages 257-261. Springer International Publishing, Cham.

DOI: 10.1007/978-3-030-23182-8_20 BibTeX

Binz, M. & Endres, D.
Where do Heuristics come from?
Proceedings of the 41st Annual Conference of the Cognitive Science
Society 2019, pages 1402-1408.

PDFlink BibTeX 

Schubert, M. & Endres, D.
Empirically Evaluating the Similarity Model of Geist, Lengnink and Wille.
Graph-Based Representation and Reasoning, pages 88-95, Cham. Springer International Publishing

DOI: 10.1007/978-3-319-91379-7 BibTeX

Velychko, D., Knopp, B. & Endres, D.
The Variational Coupled Gaussian Process Dynamical Model.
ICANN 2017, pages 291-299, Cham. Springer International Publishing

DOI: 10.1007/978-3-319-68600-4 34 BibTeX

Yegenoglu, A., Quaglio, P., Torre, E.; Grün, S. & Endres, D.
Exploring the Usefulness of Formal Concept Analysis for Robust Detection of Spatio-Temporal Spike Patterns in Massively Parallel Spike Trains.
Proceedings of ICCS 2016, Springer, 2016, 3-16
BEST PAPER AWARD

DOI: 10.1007/978-3-319-40985-6 1 BibTeX

Koch, K., Clever, D., Mombauer, K. & Endres, D.
Learning Movement Primitives from Optimal and Dynamically Feasible Trajectories for Humanoid Walking.
Proceedings of the IEEE-RAS International Conference on Humanoid Robotics (Humanoids 2015), 2015 , 866-873

DOI: 10.1109/HUMANOIDS.2015.7363463 BibTeX

Velychko, D. & Endres, D.
The variational Gaussian process dynamical model.
Proceedings of the AABI Workshop, NIPS 2015, 2015, 1-6

BibTeX

Velychko, D., Endres, D., Taubert, N. & Giese, M.
Coupling Gaussian Process Dynamical Models with Product-of-Experts Kernels.
Proceedings of the 24th International Conference on Artificial Neural Networks, LNCS 8681, Springer, 2014, 603-610

DOI: 10.1007/978-3-319-11179-7 76 BibTeX PDF

Taubert, N., Löffler, M., Ludolph, N., Christensen, A., Endres, D. & Giese, M.
A virtual reality setup for controllable, stylized real-time interactions between humans and avatars with sparse Gaussian process dynamical models.
Proceedings of the ACM Symposium on Applied Perception, 2013, 41-44

DOI: 10.1145/2492494.2492515 BibTeX PDF

Endres, D., Adam, R., Giese, M. & Noppeney, U.
Understanding the Semantic Structure of Human fMRI Brain Recordings With Formal Concept Analysis.
Proceedings of the 10h International Conference on Formal Concept Analysis (ICFCA 2012), LNAI 7278, Springer, 2012, 96-111

DOI: 10.1007/978-3-642-29892-9_13 BibTeX PDF

Taubert, N., Christensen, A., Endres, D. & Giese, M.
Online simulation of emotional interactive behaviors with hierarchical Gaussian process dynamical models.
Proceedings of the ACM Symposium on Applied Perception, ACM, 2012, 25-32

DOI: 10.1145/2338676.2338682 BibTeX PDF

Endres, D., Neumann, H., Kolesnik, M. & Giese, M.
Hooligan Detection: the Effects of Saliency and Expert Knowledge.
Proceedings of the 4th International Conference for Imaging in Crime Detection and Prevention (ICDP 2011), IET, 2011, 1-6
BEST PAPER AWARD

DOI: 10.1049/ic.2011.0131 BibTeX

Endres, D., Christensen, A., Omlor, L. & Giese, M. A.
Edelkamp, S. & Bach, J. (Eds.)
Segmentation of action streams: human observers vs. Bayesian binning.
KI 2011, LNAI 7006, Springer, 2011, 75-86
BEST APPLIED PAPER AWARD

DOI: 10.1007/978-3-642-24455-1 7 BibTeX PDF

Oberhoff, D., Endres, D., Giese, M. & Kolesnik, M.
Edelkamp, S. & Bach, J. (Eds.)
Gates for Handling Occlusion in Bayesian Models of Images.
KI2011, LNAI 7006, Springer, 2011, 228-232

DOI: 10.1007/978-3-642-24455-1 21 BibTeX PDF

Taubert, N., Endres, D., Christensen, A. & Giese, M.
Edelkamp, S. & Bach, J. (Eds.)
Shaking hands in latent space: modeling emotional interactions with Gaussian process latent variable models.
KI2011, LNAI 7006, Springer, 2011, 330-334

DOI: 10.1007/978-3-642-24455-1_32 BibTeX

Endres, D. & Földiák, P.
Koller, D.; Schuurmans, D.; Bengio, Y. & Bottou, L. (Eds.)
Interpreting the neural code with Formal Concept Analysis.
Advances in Neural Information Processing Systems 21, 2009, 425-432

URL:  http://books.nips.cc/nips21.html BibTeX

Endres, D., Földiák, P. & Priss, U.
An Application of Formal Concept Analysis to Neural Decoding.
Proceedings of the Sixth International Conference on Concept Lattices and Their Applications (CLA2008), 2009

URL: http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-433/ BibTeX PDF

Endres, D., Oram, M., Schindelin, J. & Földiák, P.
Platt, J., Koller, D., Singer, Y. & Roweis, S. (Eds.)
Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms.
Advances in Neural Information Processing Systems 20, 2008, 393-400

URL: http://books.nips.cc/nips20.html BibTeX PDF

Endres, D. & Földiák, P.
Quadratic programming for learning sparse codes.
Proceedings of the ninth international conference on artificial neural networks (ICANN99), IEE, IEE Conference Publication No. 470. London: Institution of Electrical Engineers, 1999, 2, 593-596

BibTeX PDF

Brand O., Endres D., Pfarr J.K., Berger C., Lenze S., Fiehler K. & Fleming R. (2023). The Adaptive Mind Data and Code Policy.

DOI: 10.22029/jlupub-14963

Eckert, A.-L., Gounitski, Y., Guggenmos, M. & Sterzer, P.
Cross-modality evidence for reduced choice history biases in psychosis prone individuals.
PsyArXiv, 17 Mar. 2022.

DOI: 10.31234/osf.io/tb6d3 BibTeX

Weilnhammer, V., Fritsch, M., Chikermane, M., Eckert, A.-L., Kanthak, K., Stuke, H., Kaminski, J. & Sterzer, P.
Evidence for an Active Role of Inferior Frontal Cortex in Conscious Experience.
bioRxiv.

DOI: 10.1101/2020.05.28.114645 BibTeX PDF

Weilnhammer, V., Stuke, H., Eckert, A.-L., Standvoss, K., & Sterzer, P.
Humans and mice fluctuate between external and internal modes of sensory processing.
bioRxiv.

DOI: 10.1101/2021.08.20.457079 BibTeX PDF

Meibodi, N., Abbasi, H., Schubö, A. & Endres, D.
Distracted by previous reward: integrating selection history, current task demands and saliency in a computational model.
PsyArXiv, 27 Apr. 2021.

DOI: 10.31234/osf.io/mbe5a BibTeX

Binz, M., & Endres, D. 
Emulating Human Developmental Stages with Bayesian Neural Networks.
arXiv preprint, 2019.

DOI: 10.48550/arXiv.1902.07579 BibTeX

Binz, M., & Endres, D. 
Where Do Human Heuristics Come From?
arXiv preprint, 2019.

arXiv: 1902.07580

Endres, D. (2023).
Dekodierung Mentaler Repräsentationen mit Formaler Begriffsanalyse. Presented at the lecture series of the GRK 2700, Philipps-Universität Marburg.

Endres, D. (2023).
Anwendungen der Formalen Begriffsanalyse in der Neurowissenschaft. Presented at the Festkolloquium of the Ernst-Schröder Zentrum, Technical University of Darmstadt, Germany.

Endres, D. (2019).
Models of Human Movement Perception and Production. Presented at the Technical University of Darmstadt, Germany.

Endres, D. (2019).
Models of Human Movement Perception and Production. Presented at Carl-von-Ossietzky University, Oldenburg, Germany.

Endres, D. (2018).
Analyse und Synthese menschlicher Bewegung und deren Wahrnehmung mit maschinellen Lernverfahren. Presented at the TU Chemnitz, Germany.

Endres, D. (2018).
Models of Human Movement Perception and Production. Maximilians University of Würzburg, Germany.

Endres, D. (2018).
Applications of Machine Learning in Virtual Reality. Presented at University of Applied Sciences G.S. Ohm, Nürnberg, Germany.

Endres, D. (2017).
Understanding the semantic structure of high-level vision and the basic representational units of motor control. Presented at the Brandenburgische TU Cottbus, Germany.

Endres, D. (2016).
Understanding the semantic structure of high-level vision and the basic representational units of motor control. Presented at the Cognitive Science Center, TU Darmstadt, Germany.

Endres, D. (2016).
Humanoid Walking Generation - A Novel Approach Combining Optimal Control, Movement Primitives and Learning (COCoMoPL) and its transfer to the real robot HRP-2.
Presented at the IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots, San Francisco, USA, 2016.

DOI: 10.1109/LRA.2017.2657000 BibTeX

Endres, D. (2016).
Unifying movement primitives and optimal control for efficient humanoid gait planners -- validation on HRP-2.
Presented at the Faculty of Life Sciences, University of Pretoria, South Africa, 2016.

BibTeX

D. Endres. (2016).
Unifying movement primitives and optimal control for efficient humanoid gait planners – validation in OpenHRP.
Presented at the Sports Science Colloquium, Univ. Giessen, Germany, 2016.

BibTeX

D. Clever & D. Endres. (2016).
Unifying movement primitives and optimal control for efficient humanoid gait planners – validation in OpenHRP.
Tandem Talk, presented at the ORB Colloquium, Univ. Heidelberg, Germany, 2016.

BibTeX

D. Endres. (2016).
Making the relational structure of neural data explicit with Formal Concept Analysis.
Presented at the Frankfurt Institute for Advanced Studies, Germany, 2016.

BibTeX

D. Endres. (2015).
Is human movement primitive perception Bayes-optimal?
Presented at the SFB-TRR 135/1 retreat at Rauischolzhausen Castle, Germany, 2015.

BibTeX

D. Endres. (2015).
Making the relational structure of neural data explicit with Formal Concept Analysis.
Presented at the Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience Juelich Research Centre and JARA Juelich, Germany, 2015.

BibTeX

D. Endres. (2014).
Making the latent category structure of fMRI data explicit with Formal Concept Analysis.
Presented at the Dagstuhl seminar 14381 on Neural-Symbolic Learning and Reasoning, Schloss Dagstuhl, Germany, 2014.

BibTeX

D. Endres. (2014).
Complexity determination of movement primitive extraction models.
Tutorial at the KOROIBOT summer school, Heidelberg, Germany, 2014.

BibTex

D. Endres & M.A. Giese. (2011).
Hooligan detection: the effects of saliency and expert knowledge.
Presented at the Graduiertenkolleg of the Institute of Neural Information Processing, University of Ulm, Germany, 2011.

DOI: 10.1049/ic.2011.0131 BibTeX PDF

D. Endres, J. Schindelin, P. Földiák & M. Oram. (2011).
Modelling spike trains with Bayesian binning: what do we gain by adding nonstationary rate distributions and refractory periods?
Presented at the Graduiertenkolleg of the Institute of Neural Information Processing, University of Ulm, Germany, 2011.

BibTeX

D. Endres & P. Földiák. (2009).
Interpreting the neural code with Formal Concept Analysis.
Presented at the Max-Planck Institute for biological cybernetics, Tübingen, Germany, 2009.

BibTeX

D. Endres, J. Schindelin, P. Földiák & M. Oram. (2009).
Modelling spike trains with Bayesian binning: what do we gain by adding nonstationary rate distributions and refractory periods?
Presented as an internet seminar at the University of Newcastle, UK, 2009.

BibTeX

D. Endres, J. Schindelin, P. Földiák & M. Oram. (2009).
Feature extraction from spike trains with Bayesian binning: ’latency is where the signal starts’.
Presented at the DTC workshop of the Institute of Adaptive and Neural Computation, School of Informatics, University of Edinburgh, UK, 2009.

DOI: 10.1007/s10827-009-0157-3 BibTeX

D. Endres & P. Földiák. (2008).
Interpreting the neural code with formal concept analysis.
Presented at the Hertie Institute for Clinical Brain Sciences, University Clinic Tübingen, Germany, 2008.

BibTeX PDF

D. Endres, J. Schindelin, P. Földiák & M. Oram. (2008).
Feature extraction from spike trains with Bayesian binning.
Presented at the spatiotemporal patterns and synfire chains workshop, Newcastle, UK, 2008.

BibTeX

D. Endres & P. Földiák. (2006).
Estimating mutual information by Bayesian binning.
Presented at the workshop on Methods of Information Theory in Computational Neuroscience, Computational Neuronscience Meeting (CNS), Edinburgh, UK, 2006.

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D. Endres. (2006).
Sparse coding in V1.
Presented at the University of Würzburg, Department of Physiology, Würzburg, Germany, 2006.

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D. Endres. (2005).
Project time planning using cpm/pert methods.
Presented at the University of Würzburg, Department of Psychology, Würzburg, Germany, 2005.

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Endres, D.
Exploring the Usefulness of Formal Concept Analysis for Robust Detection of Spatio-Temporal Spike Patterns in Massively Parallel Spike Trains.
Presented at the International Conference on Conceptual Structures 2016, Annecy, France, 2016.

DOI: 10.1007/978-3-319-40985-6_1 BibTeX

Endres, D.
Complexity Determination of Movement Primitive Extraction Models.
Presented at the 6th International Conference on Brain and Cognitive Engineering, Tübingen, Germany, 2014.

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Endres, D.; Smilgin, A.; Dicke P.; Giese, M. & Thier, P.
Comparing models for relating spikes to kinematic parameters in motoneurons and Purkinje cells.
Presented at the 2014 Primate Neurobiology Conference, Tübingen, Germany, 2014.

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Endres, D.; Adam, R.; Noppeney, U. & Giese, M.
Explicit coding in the brain: data-driven semantic analysis of human fMRI BOLD responses with Formal Concept Analysis.
Presented at the 35th European Conference on Visual Perception (ECVP 2012), Alghero, Italy, 2012.

DOI: 10.3389/conf.fncom.2012.55.00056 BibTeX

Endres, D.; Adam, R.; Giese, M. & Noppeney, U.
Understanding the Semantic Structure of Human fMRI Brain Recordings With Formal Concept Analysis.
Presented at the 10h International Conference on Formal Concept Analysis (ICFCA 2012), Leuven, Belgium, 2012.

DOI: 10.1007/978-3-642-29892-9_13 BibTeX PDF

Endres, D.; Neumann, H.; Kolesnik, M. & Giese, M.
Hooligan Detection: the Effects of Saliency and Expert Knowledge.
Presented at the 4th International Conference for Imaging in Crime Detection and Prevention (ICDP 2011), Kingston, UK, 2011.

DOI: 10.1049/ic.2011.0131 BibTeX

Endres, D.; Christensen, A.; Omlor, L. & Giese, M.
Segmentation of action streams: human observers vs. Bayesian binning.
Presented at the 34th Annual German Conference on AI (KI2011), Berlin, Germany, 2011

DOI: 10.1007/978-3-642-24455-1_7 BibTeX

Endres, D.; Oberhoff, D.; Giese, M. & Kolesnik, M.
Gates for Handling Occlusion in Bayesian Models of Images.
Presented at the 34th Annual German Conference on AI (KI2011), Berlin, Germany, 2011

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Taubert, N.; Endres, D.; Christensen, A. & Giese, M.
Shaking hands in latent space: modeling emotional interactions with Gaussian process latent variable models.
Presented at the 34th Annual German Conference on AI (KI2011), Berlin, Germany, 2011

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Endres, D.; Christensen, A.; Omlor, L. & Giese, M. A.
Emulating human observers with Bayesian binning: segmentation of action streams.
Presented at the Symposium on Applied Perception in Graphics and Visualization (APGV 2011), Toulouse, France, 2011

DOI: 10.1145/2010325.2010326 BibTeX PDF

Beck, T.; Wilke, C.; Wirxel, B.; Endres, D.; Lindner, A. & Giese, M.
Me or not me: Causal Inference of Agency in goal-directed actions.
Presented at the VSS annual meeting, Naples, FL, USA, 2011

DOI: 10.1167/11.11.955 BibTeX

Endres, D. & Földiák, P.
Interpreting the neural code with Formal Concept Analysis.
Presented as a poster spotlight at the Neural Information Processing Systems (NIPS) conference, Vancouver, British Columbia, Canada, 2008

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Endres, D. & Földiák, P.
Interpreting the neural code with Formal Concept Analysis: what does the structure of STSa neural responses tell us about faces?
Presented at the joint face lab meeting, University of St. Andrews, UK, 2008

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Endres, D.; Schindelin, J.; Földiák, P. & Oram, M.
Examining the joint neural code of latency and firing rate by Bayesian binning.
Presented at the Neural Coding meeting, Montevideo, Uruguay, 2007

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Endres, D.; Priss, U.; Schindelin, J. & Földiák, P.
Sparse Formal Concept Analysis.
Presented at the International Conference on Knowledge Processing in Practice (KPP), Darmstadt, Germany, 2007

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Eckert, A.-L., Guggenmos, M. & Sterzer, P.
Psychosis proneness is associated with decreased reliance on low-level prior expectations in auditory decision-making.
TeaP 2021, volume 63, page 65.

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Knopp, B.; Schubert, M. & Endres, D.
Influence of Segmentation on Movement Primitive Representations under Naturalistic Conditions.
Presented at KogWis 2019, Darmstadt, 2018
GK best poster award

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Yegenoglu, A., Quaglio, P., Torre, E., Endres, D. & Grün, S.
Spatio-Temporal Spike Pattern Recognition in Massively Parallel Spike Trains.
HBP Student Conference, Austria (Vienna), 8 Feb 2017 - 10 Feb 2017

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Müller, E.; Stolz, C. & Endres, D.
Threat-conditioned contexts modulate the late positive potential to neutral vs. angry avatars - a mobile-EEG/virtual reality study.
Presented at the Annual meeting of the Society for Psychophysical Research, Vienna, 2017

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Knopp, B.; Schubert, M. & Endres, D.
Temporal Movement Primitive Perception under Naturalistic Conditions.
Presented at the ACM Symposium for Applied Perception, Cottbus, 2017

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Stolz, C.; Endres, D. & Müller, E.
Contexts will tear us apart again: virtuelle furchtkonditionierte Kontexte modulieren das Late Positive Potential von Gesichtern.
Presented at the 43rd Conference Psychologie und Gehirn, Trier, 2017

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Fedorov, L.; Endres, D.; Vangeneuden, J. & Giese, M.
Neurodynamical model for the multi-stable perception of biological motion.
Journal of Vision, 2014 , 14(10) , 1007

DOI: 10.1167/14.10.1007 BibTeX PDF

Chiovetto, E.; Endres, D.; d’Avella , A. & Giese, M.
Model selection for the extraction of EMG synergies.
Presented at the annual meeting of the Neural Control of Movement Society, NCM. Amsterdam, The Netherlands, 2014

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Chiovetto, E.; Endres, D.; Curio, C. & Giese, M.
Perceptual integration of kinematic components for the recognition of emotional facial expressions.
Journal of Vision, 2014 , 14 (10), 205

DOI: 10.1167/14.10.205 BibTeX

Beck, T.; Endres, D.; Lindner, A. & Giese, M.
Active Sampling supported Comparison of Causal Inference Models for Agency Attribution in Goal-Directed Actions.
Journal of Vision, 2014 , 14 , 838

DOI: 10.1167/14.10.838 BibTeX

Endres, D.; Smilgin, A.; Sun, Z.; Junker, M.; Prsa, M.; Dicke, P.; Giese, M. & Thier, P.
Forces matter for relating spikes to saccade parameters in motoneurons and the oculomotor cerebellum.
Presented at the Bernstein Conference, Göttingen, Germany, 2014

DOI:10.12751/nncn.bc2014.0184 BibTeX

Beck, T.; Endres, D.; Lindner, A. & Giese, M.
Agency Attribution in Goal-Directed Actions: Active Sampling Improving Bayesian Model Comparison.
Presented at the Bernstein Conference, Göttingen, Germany, 2014

DOI: 10.12751/nncn.bc2014.0149 BibTeX

Endres, D. & Giese, M.
Testing the order-theoretic similarity model and making perceived similarity explicit with Formal Concept Analysis.
Presented at the 36th European Conference on Visual Perception, Bremen, Germany, 2013

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Endres, D.; Adam, R.; Noppeney, U. & Giese, M.
Connecting Brain and Mind with Formal Concept Analysis: a Data-Driven Semantic Investigation of the Explicit Coding Hypothesis.
Presented at the 10th German Neurobiology Meeting, Göttingen, Germany, 2013

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Endres, D.; Smilgin, A.; Dicke, P.; Giese, M. & Thier, P.
Simple spikes of Purkinje cells: pre-dictive, post-dictive or both?
Presented at the Bernstein Conference, Tübingen, Germany, 2013

DOI: 10.12751/nncn.bc2013.0221 BibTeX

Merritt, C.; Endres, D.; Weiser, A.-K.; Karnath, H.-O. & Giese, M.
Detecting errors of human action semantics using Markov logic networks as tool to quantify behavioral deficits in apraxia.
Presented at the Bernstein Conference, Tübingen, Germany, 2013

DOI: 10.12751/nncn.bc2013.0080 BibTeX

Fedorov, L.; Endres, D.; Vangeneuden, J. & Giese, M.
Neurodynamical model for the multi-stable perception of biological motion.
Presented at the Bernstein Conference, Tübingen, Germany, 2013

DOI: 10.1167/14.10.1007 BibTeX

Beck, T.; Wilke, C.; Wirxel, B.; Endres, D.; Lindner, A. & Giese, M.
Me -- not me or in between? Comparison of causal inference models for agency attribution in goal-directed actions.
Presented at the Bernstein Conference, Tübingen, Germany, 2013

DOI: 10.1167/13.9.745 BibTeX

Endres, D.; Adam, R.; Noppeney, U. & Giese, M.
Explicit coding in the brain: data-driven semantic analysis of human fMRI BOLD responses with Formal Concept Analysis.
Presented at Bernstein Conference, Munich, Germany, 2012

DOI: 10.3389/conf.fncom.2012.55.00056 BibTeX

Beck, T.; Wilke, C.; Wirxel, B.; Endres, D.; Lindner, A. & Giese, M.
Did I do it? Causal inference of authorship in goal-directed actions.
Perception ECVP suppl., 2011 , 40 , 227

DOI: 10.3389/conf.fncom.2011.53.00128 BibTeX PDF

Taubert, N.; Christensen, A.; Endres, D. & Giese, M.
Perception of synthetically generated interactive human emotional body expressions.
Perception ECVP suppl., 2012 , 41 , 101

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Beck, T.; Wilke, C.; Wirxel, B.; Endres, D.; Lindner, A. & Giese, M.
Did I do it? Causal inference of authorship in goal-directed actions for impoverished stimuli.
Perception ECVP suppl., 2012 , 41 , 255

DOI: 10.3389/conf.fncom.2012.55.00073 BibTeX

Zwanger, V.; Endres, D. & Giese, M.
Hooligan Detection: the effects of spatial and temporal expert knowledge.
Perception ECVP suppl., 2011, 40, 207

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Beck, T.; Wilke, C.; Wirxel, B.; Endres, D.; Lindner, A. & Giese, M.
Did I do it? Causal inference of agency in goal-directed actions.
Perception ECVP suppl., 2011, 40, 227

DOI: 10.3389/conf.fncom.2011.53.00128 BibTeX PDF

Endres, D. & Oram, M.
Modeling non-stationarity and inter-spike dependency in high-level visual cortical area STSa.
Presented at the 9th Göttingen meeting of the German neuroscience society, 2011

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Beck, T.; Wilke, C.; Wirxel, B.; Endres, D.; Lindner, A. & Giese, M.
A Bayesian graphical model for the influence of agency attribution on perception and control of self-action.
Presented at the 9th Göttingen meeting of the German neuroscience society, 2011

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Beck, T.; Wilke, C.; Wirxel, B.; Endres, D.; Lindner, A. & Giese, M.
It was (not) me: Causal Inference of Agency in goal-directed actions
Nature preceedings.
Presented at COSYNE, 2011

DOI: 10.1038/npre.2011.5858.2 BibTeX PDF

Endres, D.; Höffken, M.; Vintila, F.; Bruce, N.; Bouecke, J.; Kornprobst, P.; Neumann, H. & Giese, M.
Hooligan detection: the effects of saliency and expert knowledge.
Perception ECVP suppl., 2010, 39, 193

DOI: 10.1049/ic.2011.0131 BibTeX

Endres, D.; Christensen, C.; Beck, C.; Bouecke, J.; Omlor, L.; Neumann, H. & Giese, M.
Segmentation of action streams: comparison between human and statistically optimal performance.
Presented at the Vision Sciences Society 10th Annual Meeting, Naples, FL, USA, 2010

DOI: 10.1167/10.7.807 BibTeX

Endres, D. & Földiák, P.
Interpreting the neural code with Formal Concept Analysis.
Perception ECVP suppl., 2009, 38, 127

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Endres, D. & Földiák, P.
Interpreting the neural code with Formal Concept Analysis.
Presented at the Neural Information Processing Systems (NIPS) conference, Vancouver, British Columbia, Canada, 2008

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Endres, D.; Oram, M.; Schindelin, J. & Földiák, P.
Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms.
Presented at the Neural Information Processing Systems (NIPS) conference, Vancouver, British Columbia, Canada, 2007

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Oram, M.; Xiao, D. & Endres, D.
Stimulus induced decorrelation of neuronal activity in the visual system
Perception ECVP Abstract Supplement, 2007, 36

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Endres, D. & Földiák, P.
Rapid presentation is efficient for testing visual neurons (area STSa): information rate peaks in the interval [9,24] stimuli/s.
Presented at the Computational Neuronscience Meeting (CNS), Toronto, Ontario, Canada, 2007

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Endres, D. & Földiák, P.
Exact Bayesian binning and its application to neural response analysis.
Presented at the Computational and Systems Neuroscience meeting (COSYNE), Salt Lake City, Utah, USA, 2007

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Endres D., Pabst K., Eckert A.L. & Schween R. (2023). A collection of identities for variational inference with exponential-family models.

DOI: 10.17192/fdr/112

Kshirsagar A., Schween R., Sun Z. & Engel D. (2023). Multi-Joint Model of Human Upright Stance.

Available at: https://github.com/alapkshirsagar/human-posture-control

Weber, I., Niehaus, H., Krause, K., Molitor, L., Peper, M., Schmidt, L., Hakel, L., Timmermann, L., Menzler, K., Knake, S. & Oehrn, C. R. (2023)
Trust your gut: vagal nerve stimulation in humans improves reinforcement learning.
Brain Communications, 3(2).

DOI: 10.1093/braincomms/fcab039 BibTex