Specifically, ScLSTM transforms the single-cell type detection problem into a hierarchical classification problem based on feature extraction by the siamese long-short term memory (LSTM) network. The similarity matrix derived from the improved sigmoid kernel is mapped to the siamese LSTM feature space...
About this Dataset Content: This Emotion Classification dataset is designed to facilitate research and experimentation in the field of natural language processing and emotion analysis. It contains a diverse collection of text samples, each labelled with the corresponding emotion it conveys. Emotions can ...
From: ScLSTM: single-cell type detection by siamese recurrent network and hierarchical clustering Original Submission 30 Mar 2023 Submitted Original manuscript 10 May 2023 Reviewed Reviewer Report 24 May 2023 Author responded Author comments - Yabing Huang Resubmission - Version 2 24 May 2023 Submitted...
With a new proposed unit, we present a neural network (termed SC2Net) to achieve sparse codes in an end-to-end manner. To the best of our knowledge, this is one of the first works to bridge the l_1 -solver and LSTM, and may provide novel insights in understanding model-based ...
This repository includes the code for end-to-end gLSTM and sentence-conditional semantic attention, as appeared in the paper "Watch What You Just Said: Image Captioning with Text-Conditional Attention". train_new.lua is the main file for e2e-gLSTM and train_sc.lua is the main file for se...
随着电力系统中分布式能源及可调控柔性负荷等的增多,电力系统负荷的随机性增强,且电力系统智能化发展,使得可获得数据急剧增长.为充分利用历史负荷数据,提高超短期负荷的预测精度,提出一种基于attention机制的LSTM超短期负荷预测方法.首先,通过分...
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