Zobrazeno 1 - 10
of 28 510
pro vyhledávání: '"BACH, P."'
Autor:
Bach, Philipp, Chernozhukov, Victor, Klaassen, Sven, Spindler, Martin, Teichert-Kluge, Jan, Vijaykumar, Suhas
This paper advances empirical demand analysis by integrating multimodal product representations derived from artificial intelligence (AI). Using a detailed dataset of toy cars on \textit{Amazon.com}, we combine text descriptions, images, and tabular
Externí odkaz:
http://arxiv.org/abs/2501.00382
Autor:
Boccardi, B., Ricci, L., Madika, E., Bartolini, V., Bach, U., Grandi, P., Torresi, E., Krichbaum, T. P., Zensus, J. A.
In recent years, the jet formation region in active galaxies has been imaged through mm-VLBI in few ideal targets, first and foremost M87. An important leap forward for understanding jet launching could be made by identifying a larger number of suita
Externí odkaz:
http://arxiv.org/abs/2412.19268
Recent years have witnessed an emerging trend in neuromorphic computing that centers around the use of brain connectomics as a blueprint for artificial neural networks. Connectomics-based neuromorphic computing has primarily focused on embedding huma
Externí odkaz:
http://arxiv.org/abs/2412.14999
Capturing the workload of a database and replaying this workload for a new version of the database can be an effective approach for regression testing. However, false positive errors caused by many factors such as data privacy limitations, time depen
Externí odkaz:
http://arxiv.org/abs/2412.13679
Autor:
Bach, Tita Alissa, Babic, Aleksandar, Park, Narae, Sporsem, Tor, Ulfsnes, Rasmus, Smith-Meyer, Henrik, Skeie, Torkel
The maritime industry requires effective communication among diverse stakeholders to address complex, safety-critical challenges. Industrial AI, including Large Language Models (LLMs), has the potential to augment human experts' workflows in this spe
Externí odkaz:
http://arxiv.org/abs/2412.12732
Autor:
Xu, Jiachen, Li, Yushuai, Pedersen, Torben Bach, He, Yuqiang, Larsen, Kim Guldstrand, Li, Tianyi
Emerging digital twin technology has the potential to revolutionize voltage control in power systems. However, the state-of-the-art digital twin method suffers from low computational and sampling efficiency, which hinders its applications. To address
Externí odkaz:
http://arxiv.org/abs/2412.06940
Autor:
Luo, Wenqiang, Keung, Jacky Wai, Yang, Boyang, Ye, He, Goues, Claire Le, Bissyande, Tegawende F., Tian, Haoye, Le, Bach
Software systems have been evolving rapidly and inevitably introducing bugs at an increasing rate, leading to significant losses in resources consumed by software maintenance. Recently, large language models (LLMs) have demonstrated remarkable potent
Externí odkaz:
http://arxiv.org/abs/2412.01072
Prescriptive Analytics (PSA), an emerging business analytics field suggesting concrete options for solving business problems, has seen an increasing amount of interest after more than a decade of multidisciplinary research. This paper is a comprehens
Externí odkaz:
http://arxiv.org/abs/2412.00034
Autor:
Zalevskyi, Vladyslav, Sanchez, Thomas, Roulet, Margaux, Lajous, Hélène, Verdera, Jordina Aviles, Hutter, Jana, Kebiri, Hamza, Cuadra, Meritxell Bach
Fetal brain tissue segmentation in magnetic resonance imaging (MRI) is a crucial tool that supports the understanding of neurodevelopment, yet it faces challenges due to the heterogeneity of data coming from different scanners and settings, and due t
Externí odkaz:
http://arxiv.org/abs/2411.06842
There is a history of simple forecast error growth models designed to capture the key properties of error growth in operational numerical weather prediction (NWP) models. We propose here such a scalar model that relies on the previous ones and incorp
Externí odkaz:
http://arxiv.org/abs/2411.06623