Zobrazeno 1 - 10
of 20 768
pro vyhledávání: '"A. Rohrer"'
Grain growth describes the increase in the mean grain size with time during the annealing of a polycrystal; it is widely accepted that this is driven by capillarity (surface tension). Although classically modeled and interpreted as mean curvature flo
Externí odkaz:
http://arxiv.org/abs/2411.15983
Second-order optimization methods exhibit fast convergence to critical points, however, in nonconvex optimization, these methods often require restrictive step-sizes to ensure a monotonically decreasing objective function. In the presence of highly n
Externí odkaz:
http://arxiv.org/abs/2410.08033
Autor:
Ferreira, Fabio S., Ashburner, John, Bouzigues, Arabella, Suksasilp, Chatrin, Russell, Lucy L., Foster, Phoebe H., Ferry-Bolder, Eve, van Swieten, John C., Jiskoot, Lize C., Seelaar, Harro, Sanchez-Valle, Raquel, Laforce, Robert, Graff, Caroline, Galimberti, Daniela, Vandenberghe, Rik, de Mendonca, Alexandre, Tiraboschi, Pietro, Santana, Isabel, Gerhard, Alexander, Levin, Johannes, Sorbi, Sandro, Otto, Markus, Pasquier, Florence, Ducharme, Simon, Butler, Chris R., Ber, Isabelle Le, Finger, Elizabeth, Tartaglia, Maria C., Masellis, Mario, Rowe, James B., Synofzik, Matthis, Moreno, Fermin, Borroni, Barbara, Kaski, Samuel, Rohrer, Jonathan D., Mourao-Miranda, Janaina
In this study, we propose a novel approach to uncover subgroup-specific and subgroup-common latent factors addressing the challenges posed by the heterogeneity of neurological and mental disorders, which hinder disease understanding, treatment develo
Externí odkaz:
http://arxiv.org/abs/2410.07890
Autor:
Vollenweider, Michael, Schürch, Manuel, Rohrer, Chiara, Gut, Gabriele, Krauthammer, Michael, Wicki, Andreas
Precision medicine has the potential to tailor treatment decisions to individual patients using machine learning (ML) and artificial intelligence (AI), but it faces significant challenges due to complex biases in clinical observational data and the h
Externí odkaz:
http://arxiv.org/abs/2410.00509
Autor:
Naghibzadeh, S. Kiana, Xu, Zipeng, Kinderlehrer, David, Suter, Robert, Dayal, Kaushik, Rohrer, Gregory S.
Publikováno v:
Phys. Rev. Materials 8, 093403, 2024
A threshold dynamics model of grain growth that accounts for the anisotropy in the grain boundary energy has been used to simulate experimentally observed grain growth of polycrystalline Ni. The simulation reproduces several aspects of the observed m
Externí odkaz:
http://arxiv.org/abs/2409.12999
This paper presents a software component that generates a user interface structure for populating a domain ontology. The core of this work is an algorithm that takes an ontology and returns a structure describing the user interface. The component als
Externí odkaz:
http://arxiv.org/abs/2408.02130
Characteristic shock effects in silica serve as a key indicator of historical impacts at geological sites. Despite this geological significance, atomistic details of structural transformations under high pressure and shock compression remain poorly u
Externí odkaz:
http://arxiv.org/abs/2406.17676
The study of perturbations around black hole backgrounds in general relativity and Einstein-Maxwell theory has a long history, going back to the work of Regge and Wheeler in the 1950s. As part of a broader investigation of perturbations around black
Externí odkaz:
http://arxiv.org/abs/2405.11042
Silicon oxycarbides show outstanding versatility due to their highly tunable composition and microstructure. Consequently, a key challenge is a thorough knowledge of structure-property relations in the system. In this work, we fit an atomic cluster e
Externí odkaz:
http://arxiv.org/abs/2403.10154
Autor:
Menon, Sarath, Lysogorskiy, Yury, Knoll, Alexander L. M., Leimeroth, Niklas, Poul, Marvin, Qamar, Minaam, Janssen, Jan, Mrovec, Matous, Rohrer, Jochen, Albe, Karsten, Behler, Jörg, Drautz, Ralf, Neugebauer, Jörg
We present a comprehensive and user-friendly framework built upon the pyiron integrated development environment (IDE), enabling researchers to perform the entire Machine Learning Potential (MLP) development cycle consisting of (i) creating systematic
Externí odkaz:
http://arxiv.org/abs/2403.05724