Zobrazeno 1 - 10
of 3 529
pro vyhledávání: '"Hengel, P."'
Autor:
Yastrebov G. G.
Publikováno v:
Вестник Свято-Филаретовского института, Iss 47, Pp 207-216 (2023)
Externí odkaz:
https://doaj.org/article/7905da6368af472bbc82d1f00aad2c2f
Autor:
Jens Peter Ellekilde Bonde, Lea Sell, Esben Meulengracht Flachs, David Coggon, Maria Albin, Karen M Oude Hengel, Henrik Kolstad, Ingrid Sivesind Mehlum, Vivi Schlünssen, Svetlana Solovieva, Kjell Torén, Kristina Jakobsson, Christel Nielsen, Kerstin Nilsson, Lars Rylander, Kajsa Ugelvig Petersen, Sandra Søgaard Tøttenborg
Publikováno v:
Scandinavian Journal of Work, Environment & Health, Vol 49, Iss 4, p 309 (2023)
Externí odkaz:
https://doaj.org/article/fbc59b9646bc43acb5a1ea2715e8a6ad
Akademický článek
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Autor:
Cong, Gaoxiang, Pan, Jiadong, Li, Liang, Qi, Yuankai, Peng, Yuxin, Hengel, Anton van den, Yang, Jian, Huang, Qingming
Given a piece of text, a video clip, and a reference audio, the movie dubbing task aims to generate speech that aligns with the video while cloning the desired voice. The existing methods have two primary deficiencies: (1) They struggle to simultaneo
Externí odkaz:
http://arxiv.org/abs/2412.08988
Autor:
Chen, Qi, Zhao, Ruoshan, Wang, Sinuo, Phan, Vu Minh Hieu, Hengel, Anton van den, Verjans, Johan, Liao, Zhibin, To, Minh-Son, Xia, Yong, Chen, Jian, Xie, Yutong, Wu, Qi
Medical vision-and-language models (MVLMs) have attracted substantial interest due to their capability to offer a natural language interface for interpreting complex medical data. Their applications are versatile and have the potential to improve dia
Externí odkaz:
http://arxiv.org/abs/2411.12195
Autor:
Cao, Haiyao, Zou, Jinan, Liu, Yuhang, Zhang, Zhen, Abbasnejad, Ehsan, Hengel, Anton van den, Shi, Javen Qinfeng
Accurately predicting stock returns is crucial for effective portfolio management. However, existing methods often overlook a fundamental issue in the market, namely, distribution shifts, making them less practical for predicting future markets or ne
Externí odkaz:
http://arxiv.org/abs/2409.00671
Autor:
Cao, Haiyao, Zhang, Zhen, Cai, Panpan, Liu, Yuhang, Zou, Jinan, Abbasnejad, Ehsan, Huang, Biwei, Gong, Mingming, Hengel, Anton van den, Shi, Javen Qinfeng
One of the significant challenges in reinforcement learning (RL) when dealing with noise is estimating latent states from observations. Causality provides rigorous theoretical support for ensuring that the underlying states can be uniquely recovered
Externí odkaz:
http://arxiv.org/abs/2408.13498
Autor:
Chowdhury, Townim F., Phan, Vu Minh Hieu, Liao, Kewen, To, Minh-Son, Xie, Yutong, Hengel, Anton van den, Verjans, Johan W., Liao, Zhibin
The integration of vision-language models such as CLIP and Concept Bottleneck Models (CBMs) offers a promising approach to explaining deep neural network (DNN) decisions using concepts understandable by humans, addressing the black-box concern of DNN
Externí odkaz:
http://arxiv.org/abs/2408.02001
Automatically generating symbolic music-music scores tailored to specific human needs-can be highly beneficial for musicians and enthusiasts. Recent studies have shown promising results using extensive datasets and advanced transformer architectures.
Externí odkaz:
http://arxiv.org/abs/2407.04331
Autor:
Zhang, Frederic Z., Albert, Paul, Rodriguez-Opazo, Cristian, Hengel, Anton van den, Abbasnejad, Ehsan
Pre-trained models produce strong generic representations that can be adapted via fine-tuning. The learned weight difference relative to the pre-trained model, known as a task vector, characterises the direction and stride of fine-tuning. The signifi
Externí odkaz:
http://arxiv.org/abs/2407.02880