Zobrazeno 1 - 10
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pro vyhledávání: '"Chen, Wentao"'
In response to the challenges posed by the extensive parameter updates required for full fine-tuning of large-scale pre-trained models, parameter-efficient fine-tuning (PEFT) methods, exemplified by Low-Rank Adaptation (LoRA), have emerged. LoRA simp
Externí odkaz:
http://arxiv.org/abs/2405.18897
Autor:
Zhong, Linhao, Hong, Yan, Chen, Wentao, Zhou, Binglin, Zhang, Yiyi, Zhang, Jianfu, Zhang, Liqing
Text-to-image generation models have seen considerable advancement, catering to the increasing interest in personalized image creation. Current customization techniques often necessitate users to provide multiple images (typically 3-5) for each custo
Externí odkaz:
http://arxiv.org/abs/2405.16501
Dataset distillation, a pragmatic approach in machine learning, aims to create a smaller synthetic dataset from a larger existing dataset. However, existing distillation methods primarily adopt a model-based paradigm, where the synthetic dataset inhe
Externí odkaz:
http://arxiv.org/abs/2402.13007
Autor:
Chen, Wentao, Li, Jiwei, Xu, Xichen, Huang, Hui, Yuan, Siyu, Zhang, Miao, Xu, Tianming, Luo, Jie, Zhou, Weimin
[$^{18}$F]fluorodeoxyglucose (FDG) positron emission tomography (PET) has emerged as a crucial tool in identifying the epileptic focus, especially in cases where magnetic resonance imaging (MRI) diagnosis yields indeterminate results. FDG PET can pro
Externí odkaz:
http://arxiv.org/abs/2402.01191
Image-to-image translation is a common task in computer vision and has been rapidly increasing the impact on the field of medical imaging. Deep learning-based methods that employ conditional generative adversarial networks (cGANs), such as Pix2PixGAN
Externí odkaz:
http://arxiv.org/abs/2402.01186
Medical imaging systems that are designed for producing diagnostically informative images should be objectively assessed via task-based measures of image quality (IQ). Ideally, computation of task-based measures of IQ needs to account for all sources
Externí odkaz:
http://arxiv.org/abs/2402.01171
While modern biotechnologies allow synthesizing new proteins and function measurements at scale, efficiently exploring a protein sequence space and engineering it remains a daunting task due to the vast sequence space of any given protein. Protein en
Externí odkaz:
http://arxiv.org/abs/2401.06173
Autor:
Han, Xiaotian, You, Quanzeng, Liu, Yongfei, Chen, Wentao, Zheng, Huangjie, Mrini, Khalil, Lin, Xudong, Wang, Yiqi, Zhai, Bohan, Yuan, Jianbo, Wang, Heng, Yang, Hongxia
Multi-modal Large Language Models (MLLMs) are increasingly prominent in the field of artificial intelligence. These models not only excel in traditional vision-language tasks but also demonstrate impressive performance in contemporary multi-modal ben
Externí odkaz:
http://arxiv.org/abs/2311.11567
Autor:
Lu, Yao, Chen, Wentao, Zhang, Shuaining, Zhang, Kuan, Zhang, Jialiang, Zhang, Jing-Ning, Kim, Kihwan
A promising paradigm of quantum computing for achieving practical quantum advantages is quantum annealing or quantum approximate optimization algorithm, where the classical problems are encoded in Ising interactions. However, it is challenging to bui
Externí odkaz:
http://arxiv.org/abs/2311.04864
Few-shot learning is a challenging problem since only a few examples are provided to recognize a new class. Several recent studies exploit additional semantic information, e.g. text embeddings of class names, to address the issue of rare samples thro
Externí odkaz:
http://arxiv.org/abs/2303.14123