Zobrazeno 1 - 10
of 12 583
pro vyhledávání: '"Heyden, A."'
In Generalized Zero-Shot Learning (GZSL), we aim to recognize both seen and unseen categories using a model trained only on seen categories. In computer vision, this translates into a classification problem, where knowledge from seen categories is tr
Externí odkaz:
http://arxiv.org/abs/2409.00511
Autor:
Feng, Yanxia, Gerber, Dominic, Heyden, Stefanie, Kröger, Martin, Dufresne, Eric R., Isa, Lucio, Style, Robert W.
Hydrogels are particularly versatile materials that are widely found in both Nature and industry. One key reason for this versatility is their high water content, which lets them dramatically change their volume and many of their mechanical propertie
Externí odkaz:
http://arxiv.org/abs/2407.13718
Autor:
Matteucci, Federico, Arzamasov, Vadim, Cribeiro-Ramallo, Jose, Heyden, Marco, Ntounas, Konstantin, Böhm, Klemens
Experimental studies are a cornerstone of machine learning (ML) research. A common, but often implicit, assumption is that the results of a study will generalize beyond the study itself, e.g. to new data. That is, there is a high probability that rep
Externí odkaz:
http://arxiv.org/abs/2406.17374
We aim to automatize the identification of collective variables to simplify and speed up enhanced sampling simulations of conformational dynamics in biomolecules. We focus on anharmonic low-frequency vibrations that exhibit fluctuations on timescales
Externí odkaz:
http://arxiv.org/abs/2403.12174
Autor:
Karlsson, Jennie, Wodrich, Marisa, Overgaard, Niels Christian, Sahlin, Freja, Lång, Kristina, Heyden, Anders, Arvidsson, Ida
Deep learning has shown to have great potential in medical applications. In critical domains as such, it is of high interest to have trustworthy algorithms which are able to tell when reliable assessments cannot be guaranteed. Detecting out-of-distri
Externí odkaz:
http://arxiv.org/abs/2402.18960
Generalized Zero-Shot Learning (GZSL) recognizes unseen classes by transferring knowledge from the seen classes, depending on the inherent interactions between visual and semantic data. However, the discrepancy between well-prepared training data and
Externí odkaz:
http://arxiv.org/abs/2312.13100
Autor:
Heyden, Stefanie, Bain, Nicolas
The Shuttleworth equation: a linear stress-strain relation ubiquitously used in modeling the behavior of soft surfaces. Its validity in the realm of materials subject to large deformation is a topic of current debate. Here, we allow for large deforma
Externí odkaz:
http://arxiv.org/abs/2311.01896
Zero-shot Learning (ZSL) classification categorizes or predicts classes (labels) that are not included in the training set (unseen classes). Recent works proposed different semantic autoencoder (SAE) models where the encoder embeds a visual feature v
Externí odkaz:
http://arxiv.org/abs/2306.14628
Autor:
Heyden, Marco, Fouché, Edouard, Arzamasov, Vadim, Fenn, Tanja, Kalinke, Florian, Böhm, Klemens
Change detection is of fundamental importance when analyzing data streams. Detecting changes both quickly and accurately enables monitoring and prediction systems to react, e.g., by issuing an alarm or by updating a learning algorithm. However, detec
Externí odkaz:
http://arxiv.org/abs/2306.12974
We study the stochastic Budgeted Multi-Armed Bandit (MAB) problem, where a player chooses from $K$ arms with unknown expected rewards and costs. The goal is to maximize the total reward under a budget constraint. A player thus seeks to choose the arm
Externí odkaz:
http://arxiv.org/abs/2306.07071