Fabian Schrodt

Orcid: 0000-0003-2728-8326

According to our database1, Fabian Schrodt authored at least 12 papers between 2013 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2021
Gestalt Perception of Biological Motion: A Generative Artificial Neural Network Model.
Proceedings of the IEEE International Conference on Development and Learning, 2021

Binding and Perspective Taking as Inference in a Generative Neural Network Model.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2018
Neurocomputational Principles of Action Understanding: Perceptual Inference, Predictive Coding, and Embodied Simulation.
PhD thesis, 2018

2017
Mario Becomes Cognitive.
Top. Cogn. Sci., 2017

Learning Temporal Generative Neural Codes for Biological Motion Perception and Inference.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016
Just Imagine! Learning to Emulate and Infer Actions with a Stochastic Generative Architecture.
Frontiers Robotics AI, 2016

An Event-Schematic, Cooperative, Cognitive Architecture Plays Super Mario.
Proceedings of the Cognitive Robot Architectures, 2016

Is it Living? Insights from Modeling Event-Oriented, Self-Motivated, Acting, Learning and Conversing Game Agents.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

2015
Embodied learning of a generative neural model for biological motion perception and inference.
Frontiers Comput. Neurosci., 2015

2014
Modeling perspective-taking upon observation of 3D biological motion.
Proceedings of the 4th International Conference on Development and Learning and on Epigenetic Robotics, 2014

Modeling Perspective-Taking by Correlating Visual and Proprioceptive Dynamics.
Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

2013
Fully Self-Supervised Learning of an Arm Model.
Proceedings of the LWA 2013. Lernen, 2013


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