Dr. Dimitrije Markovic

Kontaktinformationen

© CC

PostDoc

Name

Dr. Dimitrije Markovic

E-Mail senden

Eine verschlüsselte E-Mail über das SecureMail-Portal versenden (nur für TUD-externe Personen).

Organisationsname

Professur für Kognitive Computationale Neurowissenschaft

Professur für Kognitive Computationale Neurowissenschaft

Adresse work

Besuchsadresse:

Falkenbrunnen, Raum 138 Chemnitzer Str. 46b

01187 Dresden

Zeige Karte von diesem Ort.

Adresse postal

Postadresse:

Technische Universität Dresden Bereich Mathematik und Naturwissenschaften
Professur für Kognitive Computationale Neurowissenschaft

01062 Dresden

work Tel.

fax Fax

+49 351 463-43147

Persönliche Webseite

See Dimitrije Markovic's personal website.

Hochschulausbildung

Wissenschaftlicher Werdegang

Veröffentlichungen

Schwöbel, S., Marković, D., Smolka, M. N., Kiebel, S. (2024) Joint modeling of choices and reaction times based on Bayesian contextual behavioral control. PLOS Computational Biology 20(7): e1012228. doi:10.1371/journal.pcbi.1012228

Marković, D., Friston, K. J., Kiebel, S. J. (2024).  Bayesian sparsification for deep neural networks with Bayesian model reduction. IEEE Access, doi:10.1109/ACCESS.2024.3417219

Markovic, D., Reiter, A. M. F., & Kiebel, S. J. (2022). Revealing human sensitivity to a latent temporal structure of changes. Frontiers in Behavioral Neuroscience, 16. doi:10.3389/fnbeh.2022.962494

Markovic, D., Stojic, H., Schwobel, S., & Kiebel, S. J. (2021). An empirical evaluation of active inference in multi-armed bandits. Neural Networks, 144, 229-246. doi:10.1016/j.neunet.2021.08.018

Markovic, D., Goschke, T., & Kiebel, S. J. (2021). Meta-control of the exploration-exploitation dilemma emerges from probabilistic inference over a hierarchy of time scales. Cognitive, Affective & Behavioral Neuroscience, 21(3), 509-533. doi:10.3758/s13415-020-00837-x

Frölich, S., Markovic, D., & Kiebel, S. J. (2021). Neuronal Sequence Models for Bayesian Online Inference. Frontiers in Artificial Intelligence. doi:10.3389/frai.2021.530937

Gros, C., Valenti, R., Schneider, L., Gutsche, B., & Markovic, D. (2021). Predicting the cumulative medical load of COVID-19 outbreaks after the peak in daily fatalities. PLoS One, 16(4), e0247272. doi:10.1371/journal.pone.0247272

Schwöbel, S., Markovic, D., Smolka, M. N., & Kiebel, S. J. (2021). Balancing control: A Bayesian interpretation of habitual and goal-directed behavior. Journal of Mathematical Psychology, 100. doi:10.1016/j.jmp.2020.102472

Frölich, S. & Markovic, D. & Kiebel, S. J. (2020). Neuronal Sequence Models for Bayesian Online Inference. https://arxiv.org/abs/2004.00930

Ott F, Marković D, Strobel A, Kiebel SJ (2020) Dynamic integration of forward planning and heuristic preferences during multiple goal pursuit. PLoS Comput Biol 16(2): e1007685. doi: 10.1371/journal.pcbi.1007685

Parr, T., Markovic, D., Kiebel, S. J., & Friston, K. J. (2019). Neuronal message passing using Mean-field, Bethe, and Marginal approximations. Scientific Reports, 9. doi:10.1038/s41598-018-38246-3

Markovic, D., & Malesevic, N. (2018). Adaptive Interface for Mapping Body Movements to Sounds. Computational Intelligence in Music, Sound, Art and Design, Evomusart 2018, 10783, 194-205. doi:10.1007/978-3-319-77583-8_13

Rivera, D. C., Ott, F., Markovic, D., Strobel, A., & Kiebel, S. J. (2018). Context-Dependent Risk Aversion: A Model-Based Approach. Frontiers in Psychology, 9. doi:10.3389/fpsyg.2018.02053

Mohr H, Zwosta K, Markovic D, Bitzer S, Wolfensteller U, et al. (2018) Deterministic response strategies in a trial-and-error learning task. PLOS Computational Biology 14(11): e1006621. doi:10.1371/journal.pcbi.1006621

Schwobel, S., Kiebel, S., & Markovic, D. (2018). Active Inference, Belief Propagation, and the Bethe Approximation. Neural Computation, 30(9), 2530-2567. doi:10.1162/neco_a_01108

Malesevic, N., Markovic, D., Kanitz, G., Controzzi, M., Cipriani, C., & Antfolk, C. (2018). Vector Autoregressive Hierarchical Hidden Markov Models for Extracting Finger Movements Using Multichannel Surface EMG Signals. Complexity. doi:10.1155/2018/9728264

Malesevic, N., Markovic, D., Kanitz, G., Controzzi, M., Cipriani, C., & Antfolk, C. (2017). Decoding of individual finger movements from surface EMG signals using Vector Autoregressive Hierarchical Hidden Markov Models (VARHHMM). 2017 International Conference on Rehabilitation Robotics (Icorr), 1518-1523.

Markovic, D., & Kiebel, S. J. (2016). Comparative Analysis of Behavioral Models for Adaptive Learning in Changing Environments. Frontiers in Computational Neuroscience, 10. doi:10.3389/fncom.2016.00033

Markovic, D., Glascher, J., Bossaerts, P., O'Doherty, J., & Kiebel, S. J. (2015). Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism. Plos Computational Biology, 11(10). doi:10.1371/journal.pcbi.1004558

Markovic, D., & Gros, C. (2014). Power laws and self-organized criticality in theory and nature. Physics Reports-Review Section of Physics Letters, 536(2), 41-74. doi:10.1016/j.physrep.2013.11.002

Markovic, D., Gros, C., & Schuelein, A. (2013). Criticality in conserved dynamical systems: Experimental observation vs. exact properties. Chaos, 23(1). doi:10.1063/1.4773003

Markovic, D., & Gros, C. (2012). Intrinsic Adaptation in Autonomous Recurrent Neural Networks. Neural Computation, 24(2), 523-540. doi:10.1162/NECO_a_00232

Gros, C., Kaczor, G., & Markovic, D. (2012). Neuropsychological constraints to human data production on a global scale. European Physical Journal B, 85(1). doi:10.1140/epjb/e2011-20581-3

Markovic, D., & Gros, C. (2010). Self-Organized Chaos through Polyhomeostatic Optimization. Physical Review Letters, 105(6). doi:10.1103/PhysRevLett.105.068702

Markovic, D., & Gros, C. (2009). Vertex routing models. New Journal of Physics, 11. doi:10.1088/1367-2630/11/7/073002