Publications

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2019

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks Journal Article

Neural Networks – Elsevier, 109 , pp. 67-80, 2019, ISBN: 0893-6080, (Impact Factor of 7.197 (2017)).

Links | BibTeX | Tags: neural network, Probabilistic Inference, RNN, spiking

Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks

2018

Gondaliya, Kaushikkumar D; Peters, Jan; Rueckert, Elmar

Learning to Categorize Bug Reports with LSTM Networks Inproceedings

Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle (VALID)., pp. 6, XPS (Xpert Publishing Services), Nice, France, 2018, ISBN: 978-1-61208-671-2, ( October 14-18, 2018).

Links | BibTeX | Tags: Natural Language Processing, neural network, RNN

Learning to Categorize Bug Reports with LSTM Networks

2017

Rueckert, Elmar; Nakatenus, Moritz; Tosatto, Samuele; Peters, Jan

Learning Inverse Dynamics Models in O(n) time with LSTM networks Inproceedings

Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

Links | BibTeX | Tags: inverse dynamics, model learning, RNN

Learning Inverse Dynamics Models in O(n) time with LSTM networks

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Efficient Online Adaptation with Stochastic Recurrent Neural Networks Inproceedings

Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

Links | BibTeX | Tags: intrinsic motivation, RNN, spiking

Efficient Online Adaptation with Stochastic Recurrent Neural Networks

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals Inproceedings

Proceedings of the Conference on Robot Learning (CoRL), 2017.

Links | BibTeX | Tags: intrinsic motivation, RNN, spiking

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals

2016

Tanneberg, Daniel; Paraschos, Alexandros; Peters, Jan; Rueckert, Elmar

Deep Spiking Networks for Model-based Planning in Humanoids Inproceedings

Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2016.

Links | BibTeX | Tags: model learning, RNN, spiking

Deep Spiking Networks for Model-based Planning in Humanoids

Rueckert, Elmar; Kappel, David; Tanneberg, Daniel; Pecevski, Dejan; Peters, Jan

Recurrent Spiking Networks Solve Planning Tasks Journal Article

Nature Publishing Group: Scientific Reports, 6 (21142), 2016.

Links | BibTeX | Tags: RNN, spiking

Recurrent Spiking Networks Solve Planning Tasks

2014

Rueckert, Elmar

Biologically inspired motor skill learning in robotics through probabilistic inference PhD Thesis

Technical University Graz, 2014.

Links | BibTeX | Tags: graphical models, locomotion, model learning, morphological compuation, movement primitives, policy search, postural control, Probabilistic Inference, Reinforcement Learning, RNN, SOC, spiking

Biologically inspired motor skill learning in robotics through probabilistic inference

Compact List without Images

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Journal Articles

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks Journal Article

Neural Networks – Elsevier, 109 , pp. 67-80, 2019, ISBN: 0893-6080, (Impact Factor of 7.197 (2017)).

Links | BibTeX

Rueckert, Elmar; Kappel, David; Tanneberg, Daniel; Pecevski, Dejan; Peters, Jan

Recurrent Spiking Networks Solve Planning Tasks Journal Article

Nature Publishing Group: Scientific Reports, 6 (21142), 2016.

Links | BibTeX

Inproceedings

Gondaliya, Kaushikkumar D; Peters, Jan; Rueckert, Elmar

Learning to Categorize Bug Reports with LSTM Networks Inproceedings

Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle (VALID)., pp. 6, XPS (Xpert Publishing Services), Nice, France, 2018, ISBN: 978-1-61208-671-2, ( October 14-18, 2018).

Links | BibTeX

Rueckert, Elmar; Nakatenus, Moritz; Tosatto, Samuele; Peters, Jan

Learning Inverse Dynamics Models in O(n) time with LSTM networks Inproceedings

Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

Links | BibTeX

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Efficient Online Adaptation with Stochastic Recurrent Neural Networks Inproceedings

Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

Links | BibTeX

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals Inproceedings

Proceedings of the Conference on Robot Learning (CoRL), 2017.

Links | BibTeX

Tanneberg, Daniel; Paraschos, Alexandros; Peters, Jan; Rueckert, Elmar

Deep Spiking Networks for Model-based Planning in Humanoids Inproceedings

Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2016.

Links | BibTeX

PhD Theses

Rueckert, Elmar

Biologically inspired motor skill learning in robotics through probabilistic inference PhD Thesis

Technical University Graz, 2014.

Links | BibTeX