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ORCIDDominik Endres
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2020 – today
- 2023
[c28]Ala Alsaleh
, Moritz Schubert, Dominik Endres:
The Effect of Sense of Agency on Self-Efficacy Beliefs: A Virtual Reality Paradigm. SAP 2023: 10:1-10:11- 2022
- [j16]Mehwish Alam, Tanya Braun, Dominik Endres, Bruno Yun:
Special issue on conceptual structures. Ann. Math. Artif. Intell. 90(11-12): 1079-1082 (2022) - [c27]Nick Augustat, Li-Ching Chuang, Christian Panitz, Christopher Stolz, Erik M. Mueller, Dominik Maria Endres:
Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach. CogSci 2022 - [c26]Neda Meibodi, Anna Schubö, Dominik Maria Endres:
Sensorimotor processes are not a source of much noise: Sensory-motor and decision components of reaction times. CogSci 2022 - [c25]Kathrin Pabst, Frederick Zittrell, Uwe Homberg, Dominik Maria Endres:
A Model for Optic Flow Integration in Locust Central-Complex Neurons Tuned to Head Direction. CogSci 2022 - [c24]Dhanaraaj Raghuveer, Dominik Maria Endres:
Formalization and Implementation of ViolEx: An Active Inference perspective. CogSci 2022 - [c23]Moritz Schubert, Dominik Maria Endres:
Extending the Bayesian Causal Inference of Body Ownership Modell Across Time. CogSci 2022 - [c22]Dhanaraaj Raghuveer, Dominik Endres:
Active Inference and Psychology of Expectations: A Study of Formalizing ViolEx. IWAI 2022: 235-250 - 2021
- [j15]Moritz Schubert, Dominik Endres:
More Plausible Models of Body Ownership Could Benefit Virtual Reality Applications. Comput. 10(9): 108 (2021) - [c21]Neda Meibodi, Hossein Abbasi, Anna Schubö, Dominik Endres:
A model of selection history in visual attention. CogSci 2021 - [c20]Moritz Schubert, Dominik Endres:
The Bayesian Causal Inference of Body Ownership Model: Use in VR and Plausible Parameter Choices. VR Workshops 2021: 67-70 - 2020
- [c19]Benjamin Knopp, Dmytro Velychko, Johannes Dreibrodt, Alexander C. Schütz, Dominik Endres:
Evaluating Perceptual Predictions based on Movement Primitive Models in VR- and Online-Experiments. SAP 2020: 1:1-1:9
2010 – 2019
- 2019
- [j14]Benjamin Knopp, Dmytro Velychko, Johannes Dreibrodt, Dominik Endres:
Predicting Perceived Naturalness of Human Animations Based on Generative Movement Primitive Models. ACM Trans. Appl. Percept. 16(3): 15:1-15:18 (2019) - [c18]Marcel Binz, Dominik Endres:
Where Do Heuristics Come From? CogSci 2019: 1402-1408 - [c17]Marcel Binz, Dominik Endres:
Emulating Human Developmental Stages with Bayesian Neural Networks. CogSci 2019: 3245 - [c16]Anna Serr, Moritz Schubert, Dominik Endres:
Mathematical Similarity Models: Do We Need Incomparability to Be Precise? ICCS 2019: 257-261 - [e2]Dominik Endres, Mehwish Alam, Diana Sotropa:
Graph-Based Representation and Reasoning - 24th International Conference on Conceptual Structures, ICCS 2019, Marburg, Germany, July 1-4, 2019, Proceedings. Lecture Notes in Computer Science 11530, Springer 2019, ISBN 978-3-030-23181-1 [contents] - [i2]Marcel Binz, Dominik Endres:
Emulating Human Developmental Stages with Bayesian Neural Networks. CoRR abs/1902.07579 (2019) - [i1]Marcel Binz, Dominik Endres:
Where Do Human Heuristics Come From? CoRR abs/1902.07580 (2019) - 2018
- [j13]Dmytro Velychko, Benjamin Knopp, Dominik Endres:
Making the Coupled Gaussian Process Dynamical Model Modular and Scalable with Variational Approximations. Entropy 20(10): 724 (2018) - [c15]Moritz Schubert, Dominik Endres:
Empirically Evaluating the Similarity Model of Geist, Lengnink and Wille. ICCS 2018: 88-95 - [e1]Peter Chapman, Dominik Endres, Nathalie Pernelle:
Graph-Based Representation and Reasoning - 23rd International Conference on Conceptual Structures, ICCS 2018, Edinburgh, UK, June 20-22, 2018, Proceedings. Lecture Notes in Computer Science 10872, Springer 2018, ISBN 978-3-319-91378-0 [contents] - 2017
- [j12]Pietro Quaglio, Alper Yegenoglu, Emiliano Torre, Dominik Endres, Sonja Grün:
Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE. Frontiers Comput. Neurosci. 11: 41 (2017) - [j11]Debora Clever, Monika Harant, Katja D. Mombaur, Maximilien Naveau, Olivier Stasse, Dominik Endres:
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 Autom. Lett. 2(2): 977-984 (2017) - [c14]Dmytro Velychko, Benjamin Knopp, Dominik Endres:
The Variational Coupled Gaussian Process Dynamical Model. ICANN (1) 2017: 291-299 - [p1]Albert Mukovskiy, Nick Taubert, Dominik Endres, Christian Vassallo, Maximilien Naveau, Olivier Stasse, Philippe Souères, Martin A. Giese:
Modeling of Coordinated Human Body Motion by Learning of Structured Dynamic Representations. Geometric and Numerical Foundations of Movements 2017: 237-267 - 2016
- [j10]Debora Clever, Monika Harant, Kai Henning Koch, Katja D. Mombaur, Dominik Endres:
A novel approach for the generation of complex humanoid walking sequences based on a combination of optimal control and learning of movement primitives. Robotics Auton. Syst. 83: 287-298 (2016) - [c13]Alper Yegenoglu, Pietro Quaglio, Emiliano Torre, Sonja Grün, Dominik Endres:
Exploring the Usefulness of Formal Concept Analysis for Robust Detection of Spatio-temporal Spike Patterns in Massively Parallel Spike Trains. ICCS 2016: 3-16 - 2015
- [c12]Kai Henning Koch, Debora Clever, Katja D. Mombaur, Dominik Endres:
Learning movement primitives from optimal and dynamically feasible trajectories for humanoid walking. Humanoids 2015: 866-873 - 2014
- [c11]Dominik Endres, Enrico Chiovetto, Martin A. Giese:
Bayesian Approaches for Learning of Primitive-Based Compact Representations of Complex Human Activities. Dance Notations and Robot Motion 2014: 117-137 - [c10]Dmytro Velychko, Dominik Endres, Nick Taubert, Martin A. Giese:
Coupling Gaussian Process Dynamical Models with Product-of-Experts Kernels. ICANN 2014: 603-610 - 2013
- [j9]Dominik Endres, Yaron Meirovitch, Tamar Flash, Martin A. Giese:
Segmenting sign language into motor primitives with Bayesian binning. Frontiers Comput. Neurosci. 7: 68 (2013) - [j8]Dominik Maria Endres, Enrico Chiovetto, Martin A. Giese:
Model selection for the extraction of movement primitives. Frontiers Comput. Neurosci. 7: 185 (2013) - [c9]Nick Taubert, Martin Löffler, Nicolas Ludolph, Andrea Christensen, Dominik Endres, Martin A. Giese:
A virtual reality setup for controllable, stylized real-time interactions between humans and avatars with sparse Gaussian process dynamical models. SAP 2013: 41-44 - 2012
- [c8]Nick Taubert, Andrea Christensen, Dominik Endres, Martin A. Giese:
Online simulation of emotional interactive behaviors with hierarchical Gaussian process dynamical models. SAP 2012: 25-32 - [c7]Dominik Endres, Ruth Adam, Martin A. Giese, Uta Noppeney:
Understanding the Semantic Structure of Human fMRI Brain Recordings with Formal Concept Analysis. ICFCA 2012: 96-111 - 2011
- [j7]Dominik Endres, Andrea Christensen, Lars Omlor, Martin A. Giese:
Emulating human observers with bayesian binning: Segmentation of action streams. ACM Trans. Appl. Percept. 8(3): 16:1-16:12 (2011) - [c6]Dominik Endres, Heiko Neumann, Marina Kolesnik, Martin A. Giese:
Hooligan detection: The effects of saliency and expert knowledge. ICDP 2011: 1-6 - [c5]Dominik Endres, Andrea Christensen, Lars Omlor, Martin A. Giese:
Segmentation of Action Streams Human Observers vs. Bayesian Binning. KI 2011: 75-86 - [c4]Daniel Oberhoff, Dominik Endres, Martin A. Giese, Marina Kolesnik:
Gates for Handling Occlusion in Bayesian Models of Images: An Initial Study. KI 2011: 228-232 - [c3]Nick Taubert, Dominik Endres, Andrea Christensen, Martin A. Giese:
Shaking Hands in Latent Space - Modeling Emotional Interactions with Gaussian Process Latent Variable Models. KI 2011: 330-334 - 2010
- [j6]Dominik Endres, Mike W. Oram:
Feature extraction from spike trains with Bayesian binning: 'Latency is where the signal starts'. J. Comput. Neurosci. 29(1-2): 149-169 (2010)
2000 – 2009
- 2009
- [j5]Dominik Maria Endres, Peter Földiák, Uta Priss:
An application of formal concept analysis to semantic neural decoding. Ann. Math. Artif. Intell. 57(3-4): 233-248 (2009) - 2008
- [j4]Dominik Endres, Peter Földiák:
Exact Bayesian bin classification: a fast alternative to Bayesian classification and its application to neural response analysis. J. Comput. Neurosci. 24(1): 21-35 (2008) - [j3]Peter Földiák, Dominik Endres:
Sparse coding. Scholarpedia 3(1): 2984 (2008) - [c2]Dominik Endres, Peter Földiák:
Interpreting the neural code with Formal Concept Analysis. NIPS 2008: 425-432 - 2007
- [c1]Dominik Endres, Mike W. Oram, Johannes E. Schindelin, Peter Földiák:
Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms. NIPS 2007: 393-400 - 2005
- [j2]Dominik Endres, Peter Földiák:
Bayesian bin distribution inference and mutual information. IEEE Trans. Inf. Theory 51(11): 3766-3779 (2005) - 2003
- [j1]Dominik Maria Endres, Johannes E. Schindelin:
A new metric for probability distributions. IEEE Trans. Inf. Theory 49(7): 1858-1860 (2003)
Coauthor Index
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