Zobrazeno 1 - 10
of 2 826
pro vyhledávání: '"Lell, A."'
Summarizing web graphs is challenging due to the heterogeneity of the modeled information and its changes over time. We investigate the use of neural networks for lifelong graph summarization. Assuming we observe the web graph at a certain time, we t
Externí odkaz:
http://arxiv.org/abs/2407.18042
Autor:
Lell, Nicolas, Scherp, Ansgar
HyperAggregation is a hypernetwork-based aggregation function for Graph Neural Networks. It uses a hypernetwork to dynamically generate weights in the size of the current neighborhood, which are then used to aggregate this neighborhood. This aggregat
Externí odkaz:
http://arxiv.org/abs/2407.11596
Text role classification involves classifying the semantic role of textual elements within scientific charts. For this task, we propose to finetune two pretrained multimodal document layout analysis models, LayoutLMv3 and UDOP, on chart datasets. The
Externí odkaz:
http://arxiv.org/abs/2402.14579
Autor:
Liu, Chang, Klein, Laura, Huang, Yixing, Baader, Edith, Lell, Michael, Kachelrieß, Marc, Maier, Andreas
To facilitate a prospective estimation of CT effective dose and risk minimization process, a prospective spatial dose estimation and the known anatomical structures are expected. To this end, a CT reconstruction method is required to reconstruct CT v
Externí odkaz:
http://arxiv.org/abs/2401.12725
Autor:
Mücke, Justin, Waldow, Daria, Metzger, Luise, Schauz, Philipp, Hoffman, Marcel, Lell, Nicolas, Scherp, Ansgar
We support scientific writers in determining whether a written sentence is scientific, to which section it belongs, and suggest paraphrasings to improve the sentence. Firstly, we propose a regression model trained on a corpus of scientific sentences
Externí odkaz:
http://arxiv.org/abs/2306.10974
Autor:
Lell, Nicolas, Scherp, Ansgar
When training a Neural Network, it is optimized using the available training data with the hope that it generalizes well to new or unseen testing data. At the same absolute value, a flat minimum in the loss landscape is presumed to generalize better
Externí odkaz:
http://arxiv.org/abs/2306.09121
Publikováno v:
Crop Journal, Vol 12, Iss 3, Pp 803-813 (2024)
Genome-wide association mapping studies (GWAS) based on Big Data are a potential approach to improve marker-assisted selection in plant breeding. The number of available phenotypic and genomic data sets in which medium-sized populations of several hu
Externí odkaz:
https://doaj.org/article/414043f0eb8b43eb80c7bfda49bd1b63
Autor:
Rodrigue Bikangui, Soulemane Parkouda, Ayong More, Marien Veraldy Magossou Mbadinga, Ismael Piérrick Mikelet Boussoukou, Georgelin Nguema Ondo, Anne Marie Mouina Nkoma, Rafiou Adamou, Yabo Josiane Honkpehedji, Elie Gide Rossatanga, Yuri Ushijima, Haruka Abe, Bertrand Lell, Jean Claude Dejon-Agobé, Jiro Yasuda, Ayola Akim Adegnika
Publikováno v:
Virology Journal, Vol 21, Iss 1, Pp 1-9 (2024)
Abstract Background Despite dengue virus (DENV) outbreak in Gabon a decade ago, less is known on the potential circulation of DENV serotypes in the country. Previous studies conducted in some areas of the country, are limited to hospital-based survey
Externí odkaz:
https://doaj.org/article/e2c9d6a78f7f41e597d8df37a6790929
Autor:
Chang Liu, Laura Klein, Yixing Huang, Edith Baader, Michael Lell, Marc Kachelrieß, Andreas Maier
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract To facilitate a prospective estimation of the effective dose of an CT scan prior to the actual scanning in order to use sophisticated patient risk minimizing methods, a prospective spatial dose estimation and the known anatomical structures
Externí odkaz:
https://doaj.org/article/e76a7cb3296f4a318f1eb2324adbb029
Privacy preserving deep learning is an emerging field in machine learning that aims to mitigate the privacy risks in the use of deep neural networks. One such risk is training data extraction from language models that have been trained on datasets, w
Externí odkaz:
http://arxiv.org/abs/2212.03749