Jan Achterhold
Jan Achterhold
Bosch Corporate Research
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Variational network quantization
J Achterhold, JM Koehler, A Schmeink, T Genewein
International Conference on Learning Representations (ICLR) 2018, 2018
Sample-efficient Cross-Entropy Method for Real-time Planning
C Pinneri, S Sawant, S Blaes, J Achterhold, J Stueckler, M Rolinek, ...
Conference on Robot Learning (CoRL) 2020, 2020
In situ measurement of part geometries in layer images from laser beam melting processes
J zur Jacobsmühlen, J Achterhold, S Kleszczynski, G Witt, D Merhof
Progress in Additive Manufacturing 4, 155-165, 2019
Numerical quadrature for probabilistic policy search
J Vinogradska, B Bischoff, J Achterhold, T Koller, J Peters
IEEE Transactions on Pattern Analysis and Machine Intelligence 42 (1), 164-175, 2018
Learning to Identify Physical Parameters from Video Using Differentiable Physics
RK Kandukuri, J Achterhold, M Möller, J Stückler
42th German Conference on Pattern Recognition (GCPR), 2020
Robust calibration marker detection in powder bed images from laser beam melting processes
J zur Jacobsmühlen, J Achterhold, S Kleszczynski, G Witt, D Merhof
2016 IEEE International Conference on Industrial Technology (ICIT), 910-915, 2016
Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
J Achterhold, J Stueckler
Conference on Artificial Intelligence and Statistics (AISTATS) 2021, 3529-3537, 2021
Learning Temporally Extended Skills in Continuous Domains as Symbolic Actions for Planning
J Achterhold, M Krimmel, J Stueckler
Conference on Robot Learning (CoRL) 2023, 2022
Physical representation learning and parameter identification from video using differentiable physics
RK Kandukuri, J Achterhold, M Moeller, J Stueckler
International Journal of Computer Vision, 1-14, 2022
Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts
J Achterhold, P Tobuschat, H Ma, D Buechler, M Muehlebach, J Stueckler
Learning for Dynamics and Control Conference, 878-890, 2023
Method, device and computer program for creating a deep neural network
J Achterhold, JM Koehler, T Genewein
US Patent 11,531,888, 2022
Planning from Images with Deep Latent Gaussian Process Dynamics
N Bosch, J Achterhold, L Leal-Taixé, J Stückler
Conference on Learning for Dynamics and Control (L4DC) 2020, 2020
Context-Conditional Navigation with a Learning-Based Terrain-and Robot-Aware Dynamics Model
S Guttikonda, J Achterhold, H Li, J Boedecker, J Stueckler
arXiv preprint arXiv:2307.09206, 2023
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