Zobrazeno 1 - 10
of 5 665
pro vyhledávání: '"Nijkamp, P."'
Integrating Artificial Intelligence (AI) into software systems has significantly enhanced their capabilities while escalating energy demands. Ensemble learning, combining predictions from multiple models to form a single prediction, intensifies this
Externí odkaz:
http://arxiv.org/abs/2405.17451
Deep learning presents novel opportunities for the auto-segmentation of gross tumor volume (GTV) in head and neck cancer (HNC), yet fully automatic methods usually necessitate significant manual refinement. This study investigates the Segment Anythin
Externí odkaz:
http://arxiv.org/abs/2402.17454
Autor:
Michiel S. Oerbekke, Robert A. de Man, Frederike G. I. van Vilsteren, Maarten W. Nijkamp, Eric Tjwa, Charlotte M. W. Gaasterland, Maarten J. van der Laan, Lotty Hooft
Publikováno v:
Orphanet Journal of Rare Diseases, Vol 19, Iss 1, Pp 1-6 (2024)
Abstract We aim to illustrate the role of complete and transparent reporting coupled with access to data sourced from published systematic reviews, especially assisting in the identification of evidence for subgroups within the context of a rare dise
Externí odkaz:
https://doaj.org/article/5291d8546b254862a053c84197d51f90
Autor:
Nijkamp, Erik, Xie, Tian, Hayashi, Hiroaki, Pang, Bo, Xia, Congying, Xing, Chen, Vig, Jesse, Yavuz, Semih, Laban, Philippe, Krause, Ben, Purushwalkam, Senthil, Niu, Tong, Kryściński, Wojciech, Murakhovs'ka, Lidiya, Choubey, Prafulla Kumar, Fabbri, Alex, Liu, Ye, Meng, Rui, Tu, Lifu, Bhat, Meghana, Wu, Chien-Sheng, Savarese, Silvio, Zhou, Yingbo, Joty, Shafiq, Xiong, Caiming
Large Language Models (LLMs) have become ubiquitous across various domains, transforming the way we interact with information and conduct research. However, most high-performing LLMs remain confined behind proprietary walls, hindering scientific prog
Externí odkaz:
http://arxiv.org/abs/2309.03450
Large language models (LLMs) have demonstrated remarkable abilities in representation learning for program synthesis and understanding tasks. The quality of the learned representations appears to be dictated by the neural scaling laws as a function o
Externí odkaz:
http://arxiv.org/abs/2305.02309
Publikováno v:
Journal of Urban Management, Vol 13, Iss 3, Pp 319-331 (2024)
Cities, towns, and rural areas form a complex spatial system influenced by governance, economic factors, and the perceptions of their residents. This paper introduces the concepts of 'cityphilia' and 'cityphobia' as metaphors for the spatial attracti
Externí odkaz:
https://doaj.org/article/af70aa887ab642aeb27eab93c1783808
Publikováno v:
Tomography, Vol 10, Iss 7, Pp 1168-1191 (2024)
Spectral photon-counting cone-beam computed tomography (CT) imaging is challenged by individual pixel response behaviours, which lead to noisy projection images and subsequent image artefacts like rings. Existing methods to correct for this either us
Externí odkaz:
https://doaj.org/article/ece8670ce05c4c2fb94eb9011c70366e
Generative models have the ability to synthesize data points drawn from the data distribution, however, not all generated samples are high quality. In this paper, we propose using a combination of coresets selection methods and ``entropic regularizat
Externí odkaz:
http://arxiv.org/abs/2302.00138
Publikováno v:
Cadernos CEPEC, Vol 13, Iss 2 (2024)
Sustainable tourism development is a major policy challenge for many cities, regions or countries. This paper describes various novel analytical ingredients to ensure a consistent and professional policy strategy in tourism destinations. In all cases
Externí odkaz:
https://doaj.org/article/9800c8c9be1d400a9c231e8a9f29619a
Publikováno v:
Journal of Transport and Land Use, Vol 17, Iss 1 (2024)
This note presents the scope and contents of a special collection in the Journal of Transport and Land Use, devoted to the theme of “Modeling Choice Behavior of Cyclists and Pedestrians in Urban Activity Space.” The aim of the special issue is to
Externí odkaz:
https://doaj.org/article/d2ed553cfac94949b3493592a7745576