Zobrazeno 1 - 10
of 5 322
pro vyhledávání: '"P. Eberle"'
Autor:
Eberle, Vincent, Guardiani, Matteo, Westerkamp, Margret, Frank, Philipp, Freyberg, Michael, Salvato, Mara, Enßlin, Torsten
The EDR and eRASS1 data have already revealed a remarkable number of undiscovered X-ray sources. Using Bayesian inference and generative modeling techniques for X-ray imaging, we aim to increase the sensitivity and scientific value of these observati
Externí odkaz:
http://arxiv.org/abs/2410.14599
Autor:
Brandl, Stephanie, Eberle, Oliver
Instruction-tuned LLMs are able to provide an explanation about their output to users by generating self-explanations that do not require gradient computations or the application of possibly complex XAI methods. In this paper, we analyse whether this
Externí odkaz:
http://arxiv.org/abs/2410.03296
Autor:
Eberle-Blick, Sarah, Pohjola, Valter
We derive a linearized version of the monotonicity method for shape reconstruction using time harmonic elastic waves. The linearized method provides an efficient version of the method, drastically reducing computation time. Here we show that the line
Externí odkaz:
http://arxiv.org/abs/2409.20339
We present and analyze a control variate strategy based on couplings to reduce the variance of finite difference estimators of sensitivity coefficients, called transport coefficients in the physics literature. We study the bias and variance of a stic
Externí odkaz:
http://arxiv.org/abs/2409.15500
Autor:
Eberle, Vincent, Guardiani, Matteo, Westerkamp, Margret, Frank, Philipp, Rüstig, Julian, Stadler, Julia, Enßlin, Torsten A.
Many advances in astronomy and astrophysics originate from accurate images of the sky emission across multiple wavelengths. This often requires reconstructing spatially and spectrally correlated signals detected from multiple instruments. To facilita
Externí odkaz:
http://arxiv.org/abs/2409.10381
We consider the Demand Strip Packing problem (DSP), in which we are given a set of jobs, each specified by a processing time and a demand. The task is to schedule all jobs such that they are finished before some deadline $D$ while minimizing the peak
Externí odkaz:
http://arxiv.org/abs/2408.08627
Autor:
Buchem, Moritz, Eberle, Franziska, Rosado, Hugo Kooki Kasuya, Schewior, Kevin, Wiese, Andreas
We consider a new scheduling problem on parallel identical machines in which the number of machines is initially not known, but it follows a given probability distribution. Only after all jobs are assigned to a given number of bags, the actual number
Externí odkaz:
http://arxiv.org/abs/2407.15737
Recent sequence modeling approaches using selective state space sequence models, referred to as Mamba models, have seen a surge of interest. These models allow efficient processing of long sequences in linear time and are rapidly being adopted in a w
Externí odkaz:
http://arxiv.org/abs/2406.07592
Autor:
Hense, Julius, Idaji, Mina Jamshidi, Eberle, Oliver, Schnake, Thomas, Dippel, Jonas, Ciernik, Laure, Buchstab, Oliver, Mock, Andreas, Klauschen, Frederick, Müller, Klaus-Robert
Multiple instance learning (MIL) is an effective and widely used approach for weakly supervised machine learning. In histopathology, MIL models have achieved remarkable success in tasks like tumor detection, biomarker prediction, and outcome prognost
Externí odkaz:
http://arxiv.org/abs/2406.04280
Autor:
Ekle, Ocheme Anthony, Eberle, William
This survey paper presents a comprehensive and conceptual overview of anomaly detection using dynamic graphs. We focus on existing graph-based anomaly detection (AD) techniques and their applications to dynamic networks. The contributions of this sur
Externí odkaz:
http://arxiv.org/abs/2406.00134