Zobrazeno 1 - 10
of 282
pro vyhledávání: '"Chen, Bo‐Yu"'
Long document summarization poses a significant challenge in natural language processing due to input lengths that exceed the capacity of most state-of-the-art pre-trained language models. This study proposes a hierarchical framework that segments an
Externí odkaz:
http://arxiv.org/abs/2410.06520
Text-to-music models allow users to generate nearly realistic musical audio with textual commands. However, editing music audios remains challenging due to the conflicting desiderata of performing fine-grained alterations on the audio while maintaini
Externí odkaz:
http://arxiv.org/abs/2407.16564
We present a nonparametric construction for deep learning compatible modern Hopfield models and utilize this framework to debut an efficient variant. Our key contribution stems from interpreting the memory storage and retrieval processes in modern Ho
Externí odkaz:
http://arxiv.org/abs/2404.03900
We present STanHop-Net (Sparse Tandem Hopfield Network) for multivariate time series prediction with memory-enhanced capabilities. At the heart of our approach is STanHop, a novel Hopfield-based neural network block, which sparsely learns and stores
Externí odkaz:
http://arxiv.org/abs/2312.17346
We introduce the sparse modern Hopfield model as a sparse extension of the modern Hopfield model. Like its dense counterpart, the sparse modern Hopfield model equips a memory-retrieval dynamics whose one-step approximation corresponds to the sparse a
Externí odkaz:
http://arxiv.org/abs/2309.12673
In this research, we propose a novel technique for visualizing nonstationarity in geostatistics, particularly when confronted with a single realization of data at irregularly spaced locations. Our method hinges on formulating a statistic that tracks
Externí odkaz:
http://arxiv.org/abs/2210.08231
While generative adversarial networks (GANs) have been widely used in research on audio generation, the training of a GAN model is known to be unstable, time consuming, and data inefficient. Among the attempts to ameliorate the training process of GA
Externí odkaz:
http://arxiv.org/abs/2209.01751
Publikováno v:
Liang you shipin ke-ji, Vol 32, Iss 1, Pp 77-81 (2024)
In order to improve the quality and reduce the loss of the nutritional content of camellia oil with the traditional press, this paper studied the process of pressing Camellia Oleifera Seeds with 10t/d Twin-Screw Oil Press. The results demonstrated th
Externí odkaz:
https://doaj.org/article/a6536bb439214587a812993dab3b77f2
Along with the evolution of music technology, a large number of styles, or "subgenres," of Electronic Dance Music(EDM) have emerged in recent years. While the classification task of distinguishing between EDM and non-EDM has been often studied in the
Externí odkaz:
http://arxiv.org/abs/2110.08862
Autor:
Chen, Bo-Yu, Hsu, Wei-Han, Liao, Wei-Hsiang, Ramírez, Marco A. Martínez, Mitsufuji, Yuki, Yang, Yi-Hsuan
A central task of a Disc Jockey (DJ) is to create a mixset of mu-sic with seamless transitions between adjacent tracks. In this paper, we explore a data-driven approach that uses a generative adversarial network to create the song transition by learn
Externí odkaz:
http://arxiv.org/abs/2110.06525