Zobrazeno 1 - 10
of 57 298
pro vyhledávání: '"P, Rudolf"'
Prototype Learning methods provide an interpretable alternative to black-box deep learning models. Approaches such as ProtoPNet learn, which part of a test image "look like" known prototypical parts from training images, combining predictive power wi
Externí odkaz:
http://arxiv.org/abs/2410.08925
Generative models lack rigorous statistical guarantees for their outputs and are therefore unreliable in safety-critical applications. In this work, we propose Sequential Conformal Prediction for Generative Models (SCOPE-Gen), a sequential conformal
Externí odkaz:
http://arxiv.org/abs/2410.01660
Autor:
Ai, Xian-Yue, Soldatov, Ivan, Oleschko, Leon, Seema, Müller, Martina, Karpitschka, Stefan, Schäfer, Rudolf, Goennenwein, Sebastian T. B.
Combining wide-field magneto-optical Kerr microscopy with a time-lapse analysis scheme allows investigating magnetization fluctuations with high spatial as well as temporal resolution. We here use this technique to study magnetization fluctuations in
Externí odkaz:
http://arxiv.org/abs/2409.15876
Autor:
van Herten, Rudolf L. M., Lagogiannis, Ioannis, Wolterink, Jelmer M., Bruns, Steffen, Meulendijks, Eva R., Dey, Damini, de Groot, Joris R., Henriques, José P., Planken, R. Nils, Saitta, Simone, Išgum, Ivana
Deep learning-based medical image segmentation and surface mesh generation typically involve a sequential pipeline from image to segmentation to meshes, often requiring large training datasets while making limited use of prior geometric knowledge. Th
Externí odkaz:
http://arxiv.org/abs/2409.11837
Autor:
Arend, Germaine, Huang, Guanhao, Feist, Armin, Yang, Yujia, Henke, Jan-Wilke, Qiu, Zheru, Jeng, Hao, Raja, Arslan Sajid, Haindl, Rudolf, Wang, Rui Ning, Kippenberg, Tobias J., Ropers, Claus
Free electrons are a widespread and universal source of electromagnetic fields. The past decades witnessed ever-growing control over many aspects of electron-generated radiation, from the incoherent emission produced by X-ray tubes to the exceptional
Externí odkaz:
http://arxiv.org/abs/2409.11300
Movement Primitives (MPs) are a well-established method for representing and generating modular robot trajectories. This work presents FA-ProDMP, a new approach which introduces force awareness to Probabilistic Dynamic Movement Primitives (ProDMP). F
Externí odkaz:
http://arxiv.org/abs/2409.11144
Publikováno v:
Eur. Phys. J. B 97, 129 (2024)
When at equilibrium, large-scale systems obey conventional thermodynamics because they belong to microscopic configurations (or states) that are typical. Crucially, the typical states usually represent only a small fraction of the total number of pos
Externí odkaz:
http://arxiv.org/abs/2409.06537
Autor:
Amarel, James, Rudolf, Christopher, Iliopoulos, Athanasios, Michopoulos, John, Smith, Leslie N.
The present paper is concerned with deep learning techniques applied to detection and localization of damage in a thin aluminum plate. We used data collected on a tabletop apparatus by mounting to the plate four piezoelectric transducers, each of whi
Externí odkaz:
http://arxiv.org/abs/2409.06084
Autor:
Weinbrenner, Paul, Klar, Patricia, Giese, Christian, Flacke, Luis, Müller, Manuel, Althammer, Matthias, Geprägs, Stephan, Gross, Rudolf, Reinhard, Friedemann
Planar scanning probe microscopy is a recently emerging alternative approach to tip-based scanning probe imaging. It can scan an extended planar sensor, such as a polished bulk diamond doped with magnetic-field-sensitive nitrogen-vacancy (NV) centers
Externí odkaz:
http://arxiv.org/abs/2409.04252
The detection of phase transitions is a fundamental challenge in condensed matter physics, traditionally addressed through analytical methods and direct numerical simulations. In recent years, machine learning techniques have emerged as powerful tool
Externí odkaz:
http://arxiv.org/abs/2409.03023