Jakob J. Hollenstein

According to our database, Jakob J. Hollenstein authored at least 14 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks.

Muthukumar Pandaram, Jakob J. Hollenstein, David Drexel, Samuele Tosatto, Antonio Jose Rodríguez-Sánchez, Justus H. Piater

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

ADRL: A reconfigurable energy-efficient transmission policy for mobile LoRa devices based on reinforcement learning.

Laura Acosta-Garcia, Juan Aznar-Poveda, Antonio-Javier García-Sánchez, Jakob J. Hollenstein, Joan García-Haro, Thomas Fahringer

Internet Things, 2025

2024

Unsupervised Learning of Effective Actions in Robotics.

Marko Zaric, Jakob J. Hollenstein, Justus H. Piater, Erwan Renaudo

CoRR, 2024

Colored Noise in PPO: Improved Exploration and Performance through Correlated Action Sampling.

Jakob J. Hollenstein, Georg Martius, Justus H. Piater

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Continual learning from demonstration of robotics skills.

Sayantan Auddy, Jakob J. Hollenstein, Matteo Saveriano, Antonio Jose Rodríguez-Sánchez, Justus H. Piater

Robotics Auton. Syst., 2023

Scalable and Efficient Continual Learning from Demonstration via Hypernetwork-generated Stable Dynamics Model.

Sayantan Auddy, Jakob J. Hollenstein, Matteo Saveriano, Antonio Jose Rodríguez-Sánchez, Justus H. Piater

CoRR, 2023

Differentiable Forward Kinematics for TensorFlow 2.

Lukas Mölschl, Jakob J. Hollenstein, Justus H. Piater

CoRR, 2023

Pink Noise Is All You Need: Colored Noise Exploration in Deep Reinforcement Learning.

Onno Eberhard, Jakob J. Hollenstein, Cristina Pinneri, Georg Martius

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Action Noise in Off-Policy Deep Reinforcement Learning: Impact on Exploration and Performance.

Jakob J. Hollenstein, Sayantan Auddy, Matteo Saveriano, Erwan Renaudo, Justus H. Piater

Trans. Mach. Learn. Res., 2022

Continual Learning from Demonstration of Robotic Skills.

Sayantan Auddy, Jakob J. Hollenstein, Matteo Saveriano, Antonio Jose Rodríguez-Sánchez, Justus H. Piater

CoRR, 2022

2020

How do Offline Measures for Exploration in Reinforcement Learning behave?

Jakob J. Hollenstein, Sayantan Auddy, Matteo Saveriano, Erwan Renaudo, Justus H. Piater

CoRR, 2020

Improving the Exploration of Deep Reinforcement Learning in Continuous Domains using Planning for Policy Search.

Jakob J. Hollenstein, Erwan Renaudo, Matteo Saveriano, Justus H. Piater

CoRR, 2020

A Visual Intelligence Scheme for Hard Drive Disassembly in Automated Recycling Routines.

Erenus Yildiz, Tobias Brinker, Erwan Renaudo, Jakob J. Hollenstein, Simon Haller-Seeber, Justus H. Piater, Florentin Wörgötter

Proceedings of the International Conference on Robotics, 2020

2013

Visual control of hidden-semi-Markov-model based acoustic speech synthesis.

Jakob J. Hollenstein, Michael Pucher, Dietmar Schabus

Proceedings of the Auditory-Visual Speech Processing, 2013