Zobrazeno 1 - 10
of 1 448
pro vyhledávání: '"A, Maucher"'
It has been shown that dipolar Bose-Einstein condensates that are tightly trapped along the polarization direction can feature a rich phase diagram. In this paper we show that finite temperature can assist in accessing parts of the phase diagram that
Externí odkaz:
http://arxiv.org/abs/2410.19260
Autor:
Eisemann, Leon, Maucher, Johannes
Publikováno v:
2024 IEEE Intelligent Vehicles Symposium (IV)
High-definition road maps play a crucial role in the functionality and verification of highly automated driving functions. These contain precise information about the road network, geometry, condition, as well as traffic signs. Despite their importan
Externí odkaz:
http://arxiv.org/abs/2407.18703
Despite tremendous progress, machine learning and deep learning still suffer from incomprehensible predictions. Incomprehensibility, however, is not an option for the use of (deep) reinforcement learning in the real world, as unpredictable actions ca
Externí odkaz:
http://arxiv.org/abs/2407.14714
We report the existence of localized states in dipolar Bose-Einstein condensates confined to a tubular geometry. We first perform a bifurcation analysis to track their emergence in a one-dimensional domain for numerical feasibility and find that loca
Externí odkaz:
http://arxiv.org/abs/2407.09177
The beyond mean-field physics due to quantum fluctuations is often described by the Lee-Huang-Yang (LHY) correction, which can be approximately written as a simple analytical expression in terms of the mean-field employing local density approximation
Externí odkaz:
http://arxiv.org/abs/2406.19609
Knowing the printer model used to print a given document may provide a crucial lead towards identifying counterfeits or conversely verifying the validity of a real document. Inkjet printers produce probabilistic droplet patterns that appear to be dis
Externí odkaz:
http://arxiv.org/abs/2407.09539
We propose a novel architecture design for video prediction in order to utilize procedural domain knowledge directly as part of the computational graph of data-driven models. On the basis of new challenging scenarios we show that state-of-the-art vid
Externí odkaz:
http://arxiv.org/abs/2407.09537
Publikováno v:
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Paris, France, 2023, pp. 1076-1084
We propose a general way to integrate procedural knowledge of a domain into deep learning models. We apply it to the case of video prediction, building on top of object-centric deep models and show that this leads to a better performance than using d
Externí odkaz:
http://arxiv.org/abs/2406.18220
Autor:
Eisemann, Leon, Maucher, Johannes
Publikováno v:
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
High-resolution road representations are a key factor for the success of (highly) automated driving functions. These representations, for example, high-definition (HD) maps, contain accurate information on a multitude of factors, among others: road g
Externí odkaz:
http://arxiv.org/abs/2405.07544
We analyse the finite-temperature phase diagram of a dipolar Bose Einstein Condensate confined in a tubular geometry. The effect of thermal fluctuations is accounted for by means of Bogoliubov theory employing the local density approximation. In the
Externí odkaz:
http://arxiv.org/abs/2402.01550