Zobrazeno 1 - 10
of 26 454
pro vyhledávání: '"Wallin, A."'
We present a new algorithm for identifying superbubbles in HI column density maps of both observed and simulated galaxies that has only a single adjustable parameter. The algorithm includes an automated galaxy-background separation step to focus the
Externí odkaz:
http://arxiv.org/abs/2409.11556
Autor:
Christensen, Christoffer Fyllgraf, Engqvist, Jonas, Wang, Fengwen, Sigmund, Ole, Wallin, Mathias
Preemptive identification of potential failure under loading of engineering structures is a critical challenge. Our study presents an innovative approach to built-in pre-failure indicators within multiscale structural designs utilizing the design fre
Externí odkaz:
http://arxiv.org/abs/2408.13113
Autor:
Allen, Julia, Alves, Bruno, Arling, Jan-Hendrik, Augsten, Kamil, Bagnaschi, Emanuele, Benato, Giovanni, Bennecke, Anna, Borca, Cecilia, Braz, Paulo, Brenner, Lydia, Degens, Jordy, Dengler, Yannick, Dimitriadi, Christina, Diociaiuti, Eleonora, Dufour, Laurent, Dunne, Patrick, Etisken, Ozgur, Ravasio, Silvia Ferrario, Fomin, Nikolai, Alonso, Andrea Garcia, Gellersen, Leif, Gsponer, Andreas, Herman, Tomas, Hiti, Bojan, Huhta, Laura, Ilg, Armin, Jarkovská, Kateřina, Jovicevic, Jelena, Keszeghova, Lucia, Kirschenmann, Henning, Klaver, Suzanne, Korajac, Arman, Kotsokechagia, Anastasia, Kussner, Meike, Lelek, Aleksandra, Lospalluto, Guiseppe, Major, Péter, Maksimovic, Veljko, Malczewski, Jakub, Benito, Carla Marin, Suarez, Paula Martinez, Milosevic, Vukasin, Modak, Atanu, Tarda, Arnau Morancho, Valero, Laura Moreno, Niel, Elisabeth, Nikiforou, Nikiforos, Novosel, Anja, Paakkinen, Petja, Pacey, Holly, Pedro, Rute, Pesut, Marko, Pietrzyk, Guillaume, Pitt, Michael, Placinta, Vlad-Mihai, Dash, Archita Rani, Räuber, Géraldine, Shopova, Mariana, Someonov, Radoslav, Simsek, Sinem, Skovpen, Kirill, Sopkova, Filomena, Souza, Fernando, Norella, Elisabetta Spadaro, Urbaniak, Marta, Gomez, Lourdes Urda, Wallin, Erik, Zaccolo, Valentina, Zardoshti, Nima, Zarnecki, Grzegorz
The European Committee for Future Accelerators (ECFA) Early-Career Researcher (ECR) panel, which represents the interests of the ECR community to ECFA, presents in this document its initiatives and activities in the year 2023. This report summarises
Externí odkaz:
http://arxiv.org/abs/2407.12761
In open-set semi-supervised learning (OSSL), we consider unlabeled datasets that may contain unknown classes. Existing OSSL methods often use the softmax confidence for classifying data as in-distribution (ID) or out-of-distribution (OOD). Additional
Externí odkaz:
http://arxiv.org/abs/2407.11735
Autor:
Tishelman-Charny, A., Affolder, A., Capocasa, F., Duden, E., Fadeyev, V., Gignac, M., Helling, C., Herde, H., Johnson, J., Lynn, D., Morii, M., Mitra, A., Poley, L., Sciolla, G., Stucci, S., Sharma, P., Van Nieuwenhuizen, G., Wallin, E., Wang, A., Wonsak, S.
At the end of Run 3 of the Large Hadron Collider (LHC), the accelerator complex will be upgraded to the High-Luminosity LHC (HL-LHC) in order to increase the total amount of data provided to its experiments. To cope with the increased rates of data,
Externí odkaz:
http://arxiv.org/abs/2407.06370
Popular regularizers with non-differentiable penalties, such as Lasso, Elastic Net, Generalized Lasso, or SLOPE, reduce the dimension of the parameter space by inducing sparsity or clustering in the estimators' coordinates. In this paper, we focus on
Externí odkaz:
http://arxiv.org/abs/2405.07677
Autor:
Bolin, David, Wallin, Jonas
The estimation of regression parameters in spatially referenced data plays a crucial role across various scientific domains. A common approach involves employing an additive regression model to capture the relationship between observations and covari
Externí odkaz:
http://arxiv.org/abs/2403.18961
Multi-object grasping is a challenging task. It is important for energy and cost-efficient operation of industrial crane manipulators, such as those used to collect tree logs off the forest floor and onto forest machines. In this work, we used synthe
Externí odkaz:
http://arxiv.org/abs/2403.11623
Autor:
Friedel, Michael J., Lautze, Nicole, Wallin, Erin, Gritto, Roland, Bonneville, Alain, Buscema, Massimo, Martel, Steve
We present a multimodal machine learning (MML) workflow to assimilate and simultaneously predict the 3d distribution of numeric and categorical features along a groundwater-geothermal continuum. Success of the MML workflow relies on a transductive le
Externí odkaz:
http://arxiv.org/abs/2312.16194
Tomographic volumetric additive manufacturing is a rapidly growing fabrication technology that enables rapid production of 3D objects through a single build step. In this process, the design of projections directly impacts geometric resolution, mater
Externí odkaz:
http://arxiv.org/abs/2312.01548