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Number of items: 4.

2022

Tanneberg, Daniel ; Peters, Jan ; Rueckert, Elmar (2022):
Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks. (Postprint)
In: Neural Networks, 109, pp. 67-80. Elsevier, ISSN 0893-6080,
DOI: 10.26083/tuprints-00020537,
[Article]

Tanneberg, Daniel ; Peters, Jan ; Rueckert, Elmar (2022):
Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals. (Publisher's Version)
In: Proceedings of Machine Learning Research, 78, In: Proceedings of the 1st Annual Conference on Robot Learning, pp. 167-174,
Darmstadt, PMLR, CoRL2017 - Conference on Robot Learning 2017, Mountain View, California, 13.-15.11.2017, DOI: 10.26083/tuprints-00020580,
[Conference or Workshop Item]

Tanneberg, Daniel ; Ploeger, Kai ; Rueckert, Elmar ; Peters, Jan (2022):
SKID RAW: Skill Discovery From Raw Trajectories. (Postprint)
In: IEEE Robotics and Automation Letters, 6 (3), pp. 4696-4703. IEEE, ISSN 2377-3774, e-ISSN 2377-3766,
DOI: 10.26083/tuprints-00020536,
[Article]

2020

Tanneberg, Daniel (2020):
Understand-Compute-Adapt: Neural Networks for Intelligent Agents. (Publisher's Version)
Darmstadt, Technische Universität Darmstadt,
DOI: 10.25534/tuprints-00017234,
[Ph.D. Thesis]

This list was generated on Mon Dec 5 07:57:13 2022 CET.