Zobrazeno 1 - 10
of 39 265
pro vyhledávání: '"A Auer"'
Accurate noise characterization is essential for reliable quantum computation. Effective Pauli noise models have emerged as powerful tools, offering detailed description of the error processes with a manageable number of parameters, which guarantees
Externí odkaz:
http://arxiv.org/abs/2412.09332
Purpose: Finding scholarly articles is a time-consuming and cumbersome activity, yet crucial for conducting science. Due to the growing number of scholarly articles, new scholarly search systems are needed to effectively assist researchers in finding
Externí odkaz:
http://arxiv.org/abs/2412.04977
Autor:
Auer, Thomas, Woittennek, Frank
A fast algorithm for planning near time-optimal trajectories for systems with an oscillatory internal dynamics has been developed in previous work. In this algorithm, trajectories are assembled from special motion primitives called jerk segments, whi
Externí odkaz:
http://arxiv.org/abs/2411.19148
Autor:
Auer, Thomas, Woittennek, Frank
An efficient approach to compute near time-optimal trajectories for linear kinematic systems with oscillatory internal dynamics is presented. Thereby, kinematic constraints with respect to velocity, acceleration and jerk are taken into account. The t
Externí odkaz:
http://arxiv.org/abs/2411.19144
Mathematical reasoning has proven to be a critical yet challenging task for large language models (LLMs), as they often struggle with complex multi-step problems. To address these limitations, we introduce the Monte Carlo Nash Equilibrium Self-Refine
Externí odkaz:
http://arxiv.org/abs/2411.15645
Autor:
Buffat, Jim, Pato, Miguel, Alonso, Kevin, Auer, Stefan, Carmona, Emiliano, Maier, Stefan, Müller, Rupert, Rademske, Patrick, Rascher, Uwe, Scharr, Hanno
We provide the first method allowing to retrieve spaceborne SIF maps at 30 m ground resolution with a strong correlation ($r^2=0.6$) to high-quality airborne estimates of sun-induced fluorescence (SIF). SIF estimates can provide explanatory informati
Externí odkaz:
http://arxiv.org/abs/2411.08925
The growing volume of biomedical scholarly document abstracts presents an increasing challenge in efficiently retrieving accurate and relevant information. To address this, we introduce a novel approach that integrates an optimized topic modelling fr
Externí odkaz:
http://arxiv.org/abs/2411.00041
Autor:
Yeung, Kylie, Gleeson, Fergus V, Schulte, Rolf F, McIntyre, Anthony, Serres, Sebastien, Morris, Peter, Auer, Dorothee, Tyler, Damian J, Grist, James T, Wiesinger, Florian
Purpose: To present a novel generalized MR image reconstruction based on pseudoinversion of the encoding matrix (Pinv-Recon) as a simple yet powerful method, and demonstrate its computational feasibility for diverse MR imaging applications. Methods:
Externí odkaz:
http://arxiv.org/abs/2410.06129
In response to the growing complexity and volume of scientific literature, this paper introduces the LLMs4Synthesis framework, designed to enhance the capabilities of Large Language Models (LLMs) in generating high-quality scientific syntheses. This
Externí odkaz:
http://arxiv.org/abs/2409.18812
This paper outlines the LLMs4OL 2024, the first edition of the Large Language Models for Ontology Learning Challenge. LLMs4OL is a community development initiative collocated with the 23rd International Semantic Web Conference (ISWC) to explore the p
Externí odkaz:
http://arxiv.org/abs/2409.10146