SQUAD 排名靠前的模型中,基本都是以词向量和字符向量共同输入到模型中的,而为了提升效果,似乎也要把字向量和词向量同时输入。但并不想将模型做得太庞大,于是在人工特征这里,加入了字符级特征。 前面介绍的 4 个特征,都是以词为基本单位来计算的,事实上也可以以字为基本单位算一次,然后把每个词内的字的结果平均...
convolutional neural network-gated recurrent unit neural networkWith the popular application of deep learning-based models in various classification problems, more and more researchers have applied these models to environmental sound classification (ESC) tasks in recent years. However, the performance of ...
Language Modeling with Gated Convolutional Networks ( GLU )理解,程序员大本营,技术文章内容聚合第一站。
论文阅读 Aspect Based Sentiment Analysis with Gated Convolutional Networks,程序员大本营,技术文章内容聚合第一站。
The first approach is a gated convolutional neural network (GCNN) as a non-recurrent network alternative. Due to its convolutional layers, the network can learn hierarchical structures in sequences, which are also present in business processes that are subject to non-linear execution patterns. The...
Tu, "Generalizing pooling functions in convolutional neural networks: Mixed, gated, and tree," in Artificial Intelligence and Statistics, 2016, pp. 464-472.Lee, C.-Y., P.W. Gallagher, and Z. Tu. Generalizing pooling functions in convolutional neural networks: Mixed, gated, and tree. in ...
Lu, Complex spectrogram enhancement by convolutional neural network with multi-metrics learning, in Proc. IEEE 27th Int. Workshop Mach. Learn. Signal Process., 2017. [7] S.-W. Fu, Y. Tsao, and X. Lu, SNR-aware convolutional neural network modeling for speech enhancement, in Proc. 17th...
This can be addressed well by Convolutional Neural Networks (CNN) which supports automatic feature extraction. It is capable of learning the global features from images effectively for image classification. But it loses the context of local information among the pixels that need to be retained for ...
DGCNN,全名为Dilate Gated Convolutional Neural Network,即“膨胀门卷积神经网络”,顾名思义,融合了两个比较新的卷积用法:膨胀卷积、门卷积,并增加了一些人工特征和trick,最终使得模型在轻、快的基础上达到最佳的效果。 该项目使用Tensorflow实现了苏剑林的博客:基于CNN的阅读理解式问答模型:DGCNN中提出的DGCNN模型。具体...
大概介绍了Convolutional Neural Networks和Vision Transformers 总结 提出一种新的用于视觉表示学习的纯ConvNet,命名为MogaNet。具体而言,设计一个空间聚合块和一个自适应channel聚合块,以在复杂度性能权衡范式下捕获上下文表示和多阶交互,广泛实验验证了MogaNet在主流视觉任务中与最先进ConvNets,ViT和混合架构相比的巨大...