Johannes Günther
Johannes Günther
Alberta Machine Intelligence Institute and University of Alberta
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Cited by
Cited by
Intelligent laser welding through representation, prediction, and control learning: An architecture with deep neural networks and reinforcement learning
J Günther, PM Pilarski, G Helfrich, H Shen, K Diepold
Mechatronics 34, 1-11, 2016
First steps towards an intelligent laser welding architecture using deep neural networks and reinforcement learning
J Günther, PM Pilarski, G Helfrich, H Shen, K Diepold
Procedia Technology 15, 474-483, 2014
Machine intelligence for adaptable closed loop and open loop production engineering systems
J Günther
Technische Universität München, 2018
Detecting the onset of machine failure using anomaly detection methods
M Riazi, O Zaiane, T Takeuchi, A Maltais, J Günther, M Lipsett
International Conference on Big Data Analytics and Knowledge Discovery, 3-12, 2019
Predictions, Surprise, and Predictions of Surprise in General Value Function Architectures
J Günther, A Kearney, MR Dawson, C Sherstan, PM Pilarski
Recurrent neural networks for pid auto-tuning
E Reichensdörfer, J Günther, K Diepold
Gamma-nets: Generalizing value estimation over timescale
C Sherstan, S Dohare, J MacGlashan, J Günther, PM Pilarski
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5717-5725, 2020
Neural Networks for fast sensor data processing in Laser Welding
J Günther, H Shen, K Diepold
Jahreskolloquium-Bildverarbeitung in der Automation, 2014
Interpretable PID parameter tuning for control engineering using general dynamic neural networks: An extensive comparison
J Günther, E Reichensdörfer, PM Pilarski, K Diepold
PLOS ONE 15(12), 2020
Automated optimization of dynamic neural network structure using genetic algorithms
C Sandner, J Günther, K Diepold
Examining the use of Temporal-Difference Incremental Delta-Bar-Delta for real-world predictive knowledge architectures
J Günther, NM Ady, A Kearney, MR Dawson, PM Pilarski
Frontiers in Robotics and AI 7, 34, 2020
Meta-learning for Predictive Knowledge Architectures: A Case Study Using TIDBD on a Sensor-rich Robotic Arm
J Günther, A Kearney, NM Ady, MR Dawson, PM Pilarski
Proceedings of the 18th International Conference on Autonomous Agents and …, 2019
Stacked denoising and stacked convolutional autoencoders
U Schmid, J Günther, K Diepold
Affordance as general value function: A computational model
D Graves, J Günther, J Luo
arXiv preprint arXiv:2010.14289, 2020
Evaluating Predictive Knowledge
A Kearney, A Koop, C Sherstan, J Gunther, RS Sutton, PM Pilarski, ...
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