Zobrazeno 1 - 10
of 78 678
pro vyhledávání: '"Zimmer, A"'
Autor:
Zimmer, Felix
There is an ongoing effort to develop feature selection algorithms to improve interpretability, reduce computational resources, and minimize overfitting in predictive models. Neural networks stand out as architectures on which to build feature select
Externí odkaz:
http://arxiv.org/abs/2410.02344
Autor:
Avila, Bryant, Augusto, Pedro, Phillips, David, Gili, Tommaso, Zimmer, Manuel, Makse, Hernán A.
Understanding the dynamical behavior of complex systems from their underlying network architectures is a long-standing question in complexity theory. Therefore, many metrics have been devised to extract network features like motifs, centrality, and m
Externí odkaz:
http://arxiv.org/abs/2409.02682
Autor:
Gili, Tommaso, Avila, Bryant, Pasquini, Luca, Holodny, Andrei, Phillips, David, Boldi, Paolo, Gabrielli, Andrea, Caldarelli, Guido, Zimmer, Manuel, Makse, Hernán A.
In his book 'A Beautiful Question', physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to the largest structures. While symmetry is a cornerstone of physics, it
Externí odkaz:
http://arxiv.org/abs/2409.02674
Autor:
Mohamed, Sondos, Zimmer, Walter, Greer, Ross, Ghita, Ahmed Alaaeldin, Castrillón-Santana, Modesto, Trivedi, Mohan, Knoll, Alois, Carta, Salvatore Mario, Marras, Mirko
Accurately detecting 3D objects from monocular images in dynamic roadside scenarios remains a challenging problem due to varying camera perspectives and unpredictable scene conditions. This paper introduces a two-stage training strategy to address th
Externí odkaz:
http://arxiv.org/abs/2408.15637
Autor:
Beck, Thomas, Baroni, Alessandro, Bennink, Ryan, Buchs, Gilles, Perez, Eduardo Antonio Coello, Eisenbach, Markus, da Silva, Rafael Ferreira, Meena, Muralikrishnan Gopalakrishnan, Gottiparthi, Kalyan, Groszkowski, Peter, Humble, Travis S., Landfield, Ryan, Maheshwari, Ketan, Oral, Sarp, Sandoval, Michael A., Shehata, Amir, Suh, In-Saeng, Zimmer, Christopher
Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era's inherent ext
Externí odkaz:
http://arxiv.org/abs/2408.16159
Autor:
Riedel, Evamaria O., de la Rosa, Ezequiel, Baran, The Anh, Petzsche, Moritz Hernandez, Baazaoui, Hakim, Yang, Kaiyuan, Robben, David, Seia, Joaquin Oscar, Wiest, Roland, Reyes, Mauricio, Su, Ruisheng, Zimmer, Claus, Boeckh-Behrens, Tobias, Berndt, Maria, Menze, Bjoern, Wiestler, Benedikt, Wegener, Susanne, Kirschke, Jan S.
Stroke remains a leading cause of global morbidity and mortality, placing a heavy socioeconomic burden. Over the past decade, advances in endovascular reperfusion therapy and the use of CT and MRI imaging for treatment guidance have significantly imp
Externí odkaz:
http://arxiv.org/abs/2408.11142
Autor:
Lu, Siqi, Guo, Junlin, Zimmer-Dauphinee, James R, Nieusma, Jordan M, Wang, Xiao, VanValkenburgh, Parker, Wernke, Steven A, Huo, Yuankai
Artificial Intelligence (AI) technologies have profoundly transformed the field of remote sensing, revolutionizing data collection, processing, and analysis. Traditionally reliant on manual interpretation and task-specific models, remote sensing has
Externí odkaz:
http://arxiv.org/abs/2408.03464
We investigate the use of derivative information for Batch Active Learning in Gaussian Process regression models. The proposed approach employs the predictive covariance matrix for selection of data batches to exploit full correlation of samples. We
Externí odkaz:
http://arxiv.org/abs/2408.01861
Autor:
Zhou, Xingcheng, Fu, Deyu, Zimmer, Walter, Liu, Mingyu, Lakshminarasimhan, Venkatnarayanan, Strand, Leah, Knoll, Alois C.
Existing roadside perception systems are limited by the absence of publicly available, large-scale, high-quality 3D datasets. Exploring the use of cost-effective, extensive synthetic datasets offers a viable solution to tackle this challenge and enha
Externí odkaz:
http://arxiv.org/abs/2407.20818
Autor:
Zimmer, Bettina, Niebuur, Bart-Jan, Schaefer, Florian, Coupette, Fabian, Tänzel, Victor, Schilling, Tanja, Kraus, Tobias
Carbon black (CB)-elastomers can serve as low-cost, highly deformable sensor materials, but hardly any work exists on their structure-property relationships. We report on flow-induced anisotropy, considering CB-silicone films generated via doctor bla
Externí odkaz:
http://arxiv.org/abs/2407.20318