Zobrazeno 1 - 10
of 9 320
pro vyhledávání: '"P. Schuh"'
Autor:
Schuh, Katharina, Souttar, Iain
We establish general conditions under which there exists uniform in time convergence between a stochastic process and its approximated system. These standardised conditions consist of a local in time estimate between the original and the approximated
Externí odkaz:
http://arxiv.org/abs/2412.05239
Autor:
Monmarché, Pierre, Schuh, Katharina
The problem of sampling according to the probability distribution minimizing a given free energy, using interacting particles unadjusted kinetic Langevin Monte Carlo, is addressed. In this setting, three sources of error arise, related to three param
Externí odkaz:
http://arxiv.org/abs/2412.03560
Fuel-lean hydrogen combustion systems hold significant potential for low pollutant emissions, but are also susceptible to intrinsic combustion instabilities. While most research on these instabilities has focused on flames without wall confinement, p
Externí odkaz:
http://arxiv.org/abs/2411.18106
At very fine grain sizes, grain boundary segregation can deviate from conventional behavior due to triple junction effects. While this issue has been addressed in prior work for substitutional alloys, here we develop a framework that accounts for int
Externí odkaz:
http://arxiv.org/abs/2411.18537
Hydrogen combustion systems operated under fuel-lean conditions offer great potential for low emissions. However, these operating conditions are also susceptible to intrinsic thermodiffusive combustion instabilities. Even though technical combustors
Externí odkaz:
http://arxiv.org/abs/2411.17590
Tailoring the nanoscale distribution of chemical species at grain boundaries is a powerful method to dramatically influence the properties of polycrystalline materials. However, classical approaches to the problem have tacitly assumed that only compe
Externí odkaz:
http://arxiv.org/abs/2411.05303
Autor:
Scomparin, Luca, Caselle, Michele, Garcia, Andrea Santamaria, Xu, Chenran, Blomley, Edmund, Dritschler, Timo, Mochihashi, Akira, Schuh, Marcel, Steinmann, Johannes L., Bründermann, Erik, Kopmann, Andreas, Becker, Jürgen, Müller, Anke-Susanne, Weber, Marc
The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution thanks to their capability of autonomously tackling a cont
Externí odkaz:
http://arxiv.org/abs/2409.16177
Accurate prediction of drug-target interactions is critical for advancing drug discovery. By reducing time and cost, machine learning and deep learning can accelerate this laborious discovery process. In a novel approach, BarlowDTI, we utilise the po
Externí odkaz:
http://arxiv.org/abs/2408.00040
Autor:
Schuh, Katharina, Whalley, Peter A.
We study three kinetic Langevin samplers including the Euler discretization, the BU and the UBU splitting scheme. We provide contraction results in $L^1$-Wasserstein distance for non-convex potentials. These results are based on a carefully tailored
Externí odkaz:
http://arxiv.org/abs/2405.09992
Cold spray coatings are the sum of countless individual bonding events between single particles impacting on top of one another at high velocities. Thus, the collective behavior of microparticles must be considered to elucidate the origins of coating
Externí odkaz:
http://arxiv.org/abs/2404.05601