Zobrazeno 1 - 10
of 13 542
pro vyhledávání: '"P. Landgraf"'
Autor:
Schrimpf, Andreas, Verbunt, Frank
Near the end of the 16th century Wilhelm IV, Landgraf von Hessen-Kassel, set up an observatory with the main goal to increase the accuracy of stellar positions primarily for use in astrology and for calendar purposes. A new star catalogue was compile
Externí odkaz:
http://arxiv.org/abs/2103.10801
Autor:
Verbunt, Frank, Schrimpf, Andreas
We analyse a manuscript star catalogue by Wilhem IV, Landgraf von Hessen-Kassel, from 1586. From measurements of altitudes and of angles between stars, given in the catalogue, we find that the measurement accuracy averages 26 arcsec for eight fundame
Externí odkaz:
http://arxiv.org/abs/2103.03034
Autor:
Luna, Cristina, Eguíluz, Augusto Gómez, Barrientos-Díez, Jorge, Moreno, Almudena, Guerra, Alba, Esquer, Manuel, Seoane, Marina L., Kay, Steven, Cameron, Angus, Camañes, Carmen, Haas, Philipp, Papantoniou, Vassilios, Wedler, Armin, Rebele, Bernhard, Reynolds, Jennifer, Landgraf, Markus
Publikováno v:
2024 International Conference on Space Robotics (iSpaRo), Luxembourg, Luxembourg, 2024, pp. 145-150
This document compiles results obtained from the test campaign of the European Moon Rover System (EMRS) project. The test campaign, conducted at the Planetary Exploration Lab of DLR in Wessling, aimed to understand the scope of the EMRS breadboard de
Externí odkaz:
http://arxiv.org/abs/2411.13978
Autor:
Haliassos, Alexandros, Mira, Rodrigo, Chen, Honglie, Landgraf, Zoe, Petridis, Stavros, Pantic, Maja
Research in auditory, visual, and audiovisual speech recognition (ASR, VSR, and AVSR, respectively) has traditionally been conducted independently. Even recent self-supervised studies addressing two or all three tasks simultaneously tend to yield sep
Externí odkaz:
http://arxiv.org/abs/2411.02256
In the field of Explainable AI (XAI), counterfactual (CF) explanations are one prominent method to interpret a black-box model by suggesting changes to the input that would alter a prediction. In real-world applications, the input is predominantly in
Externí odkaz:
http://arxiv.org/abs/2410.10463
This paper presents the open-source stochastic model predictive control framework GRAMPC-S for nonlinear uncertain systems with chance constraints. It provides several uncertainty propagation methods to predict stochastic moments of the system state
Externí odkaz:
http://arxiv.org/abs/2407.09261
Recent advances in out-of-distribution (OOD) detection on image data show that pre-trained neural network classifiers can separate in-distribution (ID) from OOD data well, leveraging the class-discriminative ability of the model itself. Methods have
Externí odkaz:
http://arxiv.org/abs/2405.17164
Evaluation of Multi-task Uncertainties in Joint Semantic Segmentation and Monocular Depth Estimation
While a number of promising uncertainty quantification methods have been proposed to address the prevailing shortcomings of deep neural networks like overconfidence and lack of explainability, quantifying predictive uncertainties in the context of jo
Externí odkaz:
http://arxiv.org/abs/2405.17097
Autor:
Drobyshev, Nikita, Casademunt, Antoni Bigata, Vougioukas, Konstantinos, Landgraf, Zoe, Petridis, Stavros, Pantic, Maja
Head avatars animated by visual signals have gained popularity, particularly in cross-driving synthesis where the driver differs from the animated character, a challenging but highly practical approach. The recently presented MegaPortraits model has
Externí odkaz:
http://arxiv.org/abs/2404.19110
In optics and photonics, a small number of building blocks, like resonators, waveguides, arbitrary couplings, and parametric interactions, allow the design of a broad variety of devices and functionalities, distinguished by their scattering propertie
Externí odkaz:
http://arxiv.org/abs/2404.14887