Encoder-decoder frameworkSpatio-temporal data miningTraffic-flow predictionAccurate human traffic prediction, as a vital component of an intelligent transportation system (ITS), can not only reduce traffic cong
Encoder-Decoder Framework 作者针对Node Embedding,提出了一个统一的Encoder-Decoder编程框架来设计和实现Graph Embedding算法,上述所述目前主流的Graph Embedding算法都可以使用该框架来重新组织代码结构。 Encoder:目标是将每个Node映射编码成低维的向量表示,或embedding。 Decoder:目标是利用Encoder输出的Embedding,来解码关于...
This section presents the quantitative and qualitative results of the proposed method using three different datasets. In the quantitative results, the proposed framework performance of the multiclass segmentation and the single-class segmentation is compared with the different approaches using the JSRT data...
such as in end-to-end neural machine translation models and speech recognition models. Motivated by the success of T5 (Text-To-Text Transfer Transformer) in pre-trained natural language processing models, the researchers proposed a unified-modal SpeechT5...
该研究团队近年来一直致力于语音解码的研究,与Facebook等在这一领域有密切合作,相信不久还会有新的成果,值得期待。 原文:Machine translation of cortical activity to text with an encoder–decoder framework
MobileCount: An Efficient Encoder-Decoder Framework for Real-Time Crowd CountingCrowd countingLight-weight neural networksFully convolutional networksIn this work, we propose a computation-efficient encoder-decoder architecture, named MobileCount, which is specifically designed for high-accuracy real-time ...
每个entity memory是一个embedding table, αi 计算对每个外部entity的注意力, hsent是 将外部entity信息集成进模型的hidden state中 2.Pre-Training Objective LM objective: (1)随机mask补全 (2)随机mask实体并补全 实体链接 objective: 用维基百科中出现的实体超链接作为golden label 同时使用别名表来匹配发布...
Machine translation of cortical activity to text with an encoder–decoder framework. Nat Neurosci 23, 575–582 (2020). https://doi.org/10.1038/s41593-020-0608-8 Download citation Received23 August 2019 Accepted10 February 2020 Published30 March 2020 Issue DateApril 2020 DOIhttps://doi.org/...
encoder-decoder framework in mid- and long-term daily streamflow forecasting. To address these issues and further enhance the capability of common VMD-LSTM model in mid and long-term streamflow forecasting, we have developed a novel and efficient forecast model VMD-LSTM-ED by integrating VMD and...
In this context, this work proposes a physics-informed encoder-decoder framework for predictive carbon emissions estimation. The input variables are transformed into sequences to extract essential features and time information in the encoder, where the decoder receives the sequence and makes a ...