Research output

31 - 40 out of 255Page size: 10

Sort by: Publication date

2022
Published
Quantification of Transfer in Reinforcement Learning via Regret Bounds for Learning Agents
Tuynman, A. & Ortner, R., Sept 2022.
Research output: Contribution to conference › Poster › Research › peer-review
Published
Regret Bounds for Satisficing in Multi-Armed Bandit Problems
Michel, T., Hajiabolhassan, H. & Ortner, R., Sept 2022.
Research output: Contribution to conference › Poster › Research › peer-review
Published
Predicting Packaging Sizes Using Machine Learning
Heininger, M. & Ortner, R., 22 Aug 2022, In: Operations research forum. 43.2022, 3, 14 p., 43.
Research output: Contribution to journal › Article › Research › peer-review
E-pub ahead of print
Holistic autonomous model for early detection of downhole drilling problems in real-time
Elmgerbi, A. & Thonhauser, G., 20 Jun 2022, (E-pub ahead of print) In: Process safety and environmental protection. 164.2022, August, p. 418-434 17 p.
Research output: Contribution to journal › Article › Research › peer-review
Published
Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics
Xue, H., Hein, B., Bakr, M., Schildbach, G., Abel, B. & Rueckert, E., 19 Mar 2022, In: Applied Sciences : open access journal. 12.2022, 6, 30 p., 3153.
Research output: Contribution to journal › Article › Research › peer-review
Published
Machine Learning Techniques Application for Real-Time Drilling Hydraulic Optimization
Elmgerbi, A., Thonhauser, G., Nascimento, A. & Chuykov, E., 21 Feb 2022.
Research output: Contribution to conference › Paper
Published
DETECTING DOWNHOLE DRILLING EVENTS
Elmgerbi, A. & Thonhauser, G., 3 Feb 2022, IPC No. E21B 47/ 06 A I, Patent No. WO2022022812, Priority date 28 Jul 2020, Priority No. WO2020EP71284
Research output: Patent
2021
Published
A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning
Denz, R., Demirci, R., Cansev, M. E., Bliek, A., Beckerle, P., Rueckert, E. & Rottmann, N., 6 Dec 2021, In: Proceedings of the International Conference on Advanced Robotics. p. 1109-1115 7 p.
Research output: Contribution to journal › Conference article › peer-review
Published
Implementing the autonomous adaptive algorithm to manage ESP operation in harsh reservoir conditions
Antonic, M., Solesa, M., Thonhauser, G., Aleksic, M. & Zolotukhin, A., 25 Nov 2021.
Research output: Contribution to conference › Paper › peer-review
Published
Using Probabilistic Movement Primitives in Analyzing Human Motion Differences Under Transcranial Current Stimulation
Xue, H., Herzog, R., Berger, T. M., Bäumer, T., Weissbach, A. & Rueckert, E., 14 Sept 2021, In: Frontiers in robotics and AI. 8.2021, 18 p., 721890.
Research output: Contribution to journal › Article › Research › peer-review

Previous 1 2 3 4 5 6 7 8 ...26 Next

Research Portal

Research output

Quantification of Transfer in Reinforcement Learning via Regret Bounds for Learning Agents

Regret Bounds for Satisficing in Multi-Armed Bandit Problems

Predicting Packaging Sizes Using Machine Learning

Holistic autonomous model for early detection of downhole drilling problems in real-time

Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics

Machine Learning Techniques Application for Real-Time Drilling Hydraulic Optimization

DETECTING DOWNHOLE DRILLING EVENTS

A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning

Implementing the autonomous adaptive algorithm to manage ESP operation in harsh reservoir conditions

Using Probabilistic Movement Primitives in Analyzing Human Motion Differences Under Transcranial Current Stimulation

Advanced filters