Zobrazeno 1 - 10
of 1 742
pro vyhledávání: '"Metze, P."'
Deep learning models like Convolutional Neural Networks and transformers have shown impressive capabilities in speech verification, gaining considerable attention in the research community. However, CNN-based approaches struggle with modeling long-se
Externí odkaz:
http://arxiv.org/abs/2412.10989
Autor:
Alberto Canarini, Lucia Fuchslueger, Jörg Schnecker, Dennis Metze, Daniel B. Nelson, Ansgar Kahmen, Margarete Watzka, Erich M. Pötsch, Andreas Schaumberger, Michael Bahn, Andreas Richter
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Microbial growth is central to soil carbon cycling. However, how microbial communities grow under climate change is still largely unexplored. Here we use a unique field experiment simulating future climate conditions (increased atmospheric C
Externí odkaz:
https://doaj.org/article/39442f5a167147f3b352420dc3399d8d
Autor:
Picetti, Francesco, Deshpande, Shrinath, Leban, Jonathan, Shahtalebi, Soroosh, Patel, Jay, Jing, Peifeng, Wang, Chunpu, Metze III, Charles, Sun, Cameron, Laidlaw, Cera, Warren, James, Huynh, Kathy, Page, River, Hogins, Jonathan, Crespi, Adam, Ganguly, Sujoy, Ebadi, Salehe Erfanian
We present a novel human body model formulated by an extensive set of anthropocentric measurements, which is capable of generating a wide range of human body shapes and poses. The proposed model enables direct modeling of specific human identities th
Externí odkaz:
http://arxiv.org/abs/2309.03812
Publikováno v:
JEADV Clinical Practice, Vol 3, Iss 5, Pp 1653-1655 (2024)
Abstract Hailey–Hailey disease (HHD) is a genetic skin disorder, accompanied by lesional pruritus and a relevant impact on quality of life of affected patients. Approved or even successful treatments are still lacking, highlighting the need for fur
Externí odkaz:
https://doaj.org/article/93fb029b7a964a4181954b0ffa426230
Autor:
Arthur Gomes Oliveira Braga, Katia Borgia Barbosa Pagnano, Marina Dal'Bó Pelegrini Campioni, Ana Beatriz Pascoal Lopes, Gislaine Oliveira Duarte, Konradin Metze, Irene Lorand-Metze
Publikováno v:
Hematology, Transfusion and Cell Therapy, Vol 46, Iss 3, Pp 268-272 (2024)
Introduction: Treatment-free remission (TFR) is successful in half of the patients with chronic myeloid leukemia who discontinue Imatinib (IM) after sustained molecular response. Methods: In a prospective trial, we used pioglitazone for 3 months befo
Externí odkaz:
https://doaj.org/article/844ca4a2161b431180b6697474d2849e
Autor:
Christian Pfrepper MD, Careen Franke MD, Michael Metze MD, Maria Weise MD, Annelie Siegemund PhD, Roland Siegemund PhD, Martin Federbusch MD, Reinhard Henschler MD, Sirak Petros MD, Manuela Konert MD
Publikováno v:
Clinical and Applied Thrombosis/Hemostasis, Vol 30 (2024)
The Total Thrombus-formation Analysis System (T-TAS) is an automated device using coated microchips to assess thrombus formation under flow conditions. Its value to monitor coagulation function in patients under antiplatelet therapy awaits further cl
Externí odkaz:
https://doaj.org/article/e2e81f5887f14b8fa94a3733e0194ed6
Autor:
Lina Renkhold, Manuel P. Pereira, Karin Loser, Dieter Metze, Daniel Baeumer, Nima Melzer, Maximilian Reinhardt, Athanasios Tsianakas, Thomas Luger, Christian Mess, Ruth Becker, Clara Hambüchen, Konstantin Agelopoulos, Sonja Ständer
Publikováno v:
Acta Dermato-Venereologica, Vol 104 (2024)
The occurrence of pruritus in psoriasis was previously underestimated but is a significant burden. Secukinumab (SEC), a monoclonal anti-interleukin-17A antibody, efficiently controls signs of psoriasis, but the effect on pruritus and cutaneous neuroa
Externí odkaz:
https://doaj.org/article/be7c76688d574b3cbb0b60bd456fa808
Quantization has become a predominant approach for model compression, enabling deployment of large models trained on GPUs onto smaller form-factor devices for inference. Quantization-aware training (QAT) optimizes model parameters with respect to the
Externí odkaz:
http://arxiv.org/abs/2212.05603
Autor:
Park, Yookoon, Azab, Mahmoud, Xiong, Bo, Moon, Seungwhan, Metze, Florian, Kundu, Gourab, Ahmed, Kirmani
Cross-modal contrastive learning has led the recent advances in multimodal retrieval with its simplicity and effectiveness. In this work, however, we reveal that cross-modal contrastive learning suffers from incorrect normalization of the sum retriev
Externí odkaz:
http://arxiv.org/abs/2212.11790
Autor:
Arora, Siddhant, Dalmia, Siddharth, Yan, Brian, Metze, Florian, Black, Alan W, Watanabe, Shinji
End-to-end spoken language understanding (SLU) systems are gaining popularity over cascaded approaches due to their simplicity and ability to avoid error propagation. However, these systems model sequence labeling as a sequence prediction task causin
Externí odkaz:
http://arxiv.org/abs/2210.15734