Zobrazeno 1 - 10
of 288
pro vyhledávání: '"WOLF, VERENA"'
In recent years, a wide variety of graph neural network (GNN) architectures have emerged, each with its own strengths, weaknesses, and complexities. Various techniques, including rewiring, lifting, and node annotation with centrality values, have bee
Externí odkaz:
http://arxiv.org/abs/2410.08759
We propose an extension of the reinforcement learning architecture that enables moral decision-making of reinforcement learning agents based on normative reasons. Central to this approach is a reason-based shield generator yielding a moral shield tha
Externí odkaz:
http://arxiv.org/abs/2409.15014
Autor:
Wolf, Verena
Young stellar objects (YSOs) accrete up to half of their material in short periods of enhanced mass accretion. For massive YSOs (MYSOs with more than 8 solar masses), accretion outbursts are of special importance, as they serve as diagnostics in high
Externí odkaz:
http://arxiv.org/abs/2405.17048
Autor:
Thrän, Daniela, Arendt, Oliver, Ponitka, Jens, Braun, Julian, Millinger, Markus, Wolf, Verena, Banse, Martin, Schaldach, Rüdiger, Schüngel, Jan, Gärtner, Sven, Rettenmaier, Nils, Hünecke, Katja, Hennenberg, Klaus, Wern, Bernhard, Baur, Frank, Fritsche, Uwe, Gress, Hans-Werner
This publication is the English version of the summary of the German report „Meilensteine 2030“ (THRÄN et al. 2015) which is published in the series of the funding programme “Biomass energy use”. The report describes elements and milestones
Externí odkaz:
https://slub.qucosa.de/id/qucosa%3A80300
https://slub.qucosa.de/api/qucosa%3A80300/attachment/ATT-0/
https://slub.qucosa.de/api/qucosa%3A80300/attachment/ATT-0/
Autor:
Thrän, Daniela, Arendt, Oliver, Ponitka, Jens, Braun, Julian, Millinger, Markus, Wolf, Verena, Banse, Martin, Schaldach, Rüdiger, Schüngel, Jan, Gärtner, Sven, Rettenmaier, Nils, Hünecke, Katja, Hennenberg, Klaus, Wern, Bernhard, Baur, Frank, Fritsche, Uwe, Gress, Hans-Werner
Publikováno v:
Schriftenreihe des BMU-Förderprogramms Energetische Biomassenutzung.
In einer weitgehend auf erneuerbaren Energien fußenden Energieversorgung in Deutschland muss Bioenergie künftig die Lücken füllen, die nicht aus anderen Quellen gespeist werden können – diese These hat die Diskussion um Bioenergie im beginnend
Externí odkaz:
https://slub.qucosa.de/id/qucosa%3A79942
https://slub.qucosa.de/api/qucosa%3A79942/attachment/ATT-0/
https://slub.qucosa.de/api/qucosa%3A79942/attachment/ATT-0/
Monte Carlo estimation in plays a crucial role in stochastic reaction networks. However, reducing the statistical uncertainty of the corresponding estimators requires sampling a large number of trajectories. We propose control variates based on the s
Externí odkaz:
http://arxiv.org/abs/2110.09143
Dynamical systems in which local interactions among agents give rise to complex emerging phenomena are ubiquitous in nature and society. This work explores the problem of inferring the unknown interaction structure (represented as a graph) of such a
Externí odkaz:
http://arxiv.org/abs/2105.14329
To understand the long-run behavior of Markov population models, the computation of the stationary distribution is often a crucial part. We propose a truncation-based approximation that employs a state-space lumping scheme, aggregating states in a gr
Externí odkaz:
http://arxiv.org/abs/2105.01536
Many probabilistic inference problems such as stochastic filtering or the computation of rare event probabilities require model analysis under initial and terminal constraints. We propose a solution to this bridging problem for the widely used class
Externí odkaz:
http://arxiv.org/abs/2010.10096
Learning-based approaches for solving large sequential decision making problems have become popular in recent years. The resulting agents perform differently and their characteristics depend on those of the underlying learning approach. Here, we cons
Externí odkaz:
http://arxiv.org/abs/2008.00766