RNN models for image generation MARCH 3, 2017   Today we’re looking at the remaining papers from the unsupervised learning and generative networks section of the ‘top 100 awesome deep learning papers‘ collection. These are: DRAW: A recurrent neural n…

转载 - Recurrent Neural Networks Tutorial, Part 2 – Implementing a RNN with Python, Numpy and Theano 本文是RNN教程的第二部分,第一部分教程在这里. 对应的样板代码在 Github上面. 在这部分内容中,我将会使用 numpy 和 theano 从头开始实现RNN 模型. 实验中涉及的代码可以在Github中找到.一些不重要的内容将会略去,但是Github中保留了全部的实践过程. 语言建模 Our…

http://karpathy.github.io/2015/05/21/rnn-effectiveness/ There’s something magical about Recurrent Neural Networks (RNNs). I still remember when I trained my first recurrent network for Image Captioning. Within a few dozen minutes of training my first…

Abstract Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. 语义词空间是非常有用的,但它不能有原则地表达较长短语的意义. Further progress towards understanding compositionality in tasks such as sentiment detection requ…

Awesome-Pytorch-list 2018-08-10 09:25:16 This blog is copied from: https://github.com/Epsilon-Lee/Awesome-pytorch-list Pytorch & related libraries pytorch : Tensors and Dynamic neural networks in Python with strong GPU acceleration. pytorch extras :…

(论文编号及摘要见 [2017 ACL] 对话系统. [2018 ACL Long] 对话系统. 论文标题[]中最后的数字表示截止2019.1.21 google被引次数) 1. Domain Adaptation: challenges: (a) data shifts (syn -> live user data; stale -> current) cause distribution mismatch bet train and eval. -> 2017.1 (b) reest…

R2RT   Written Memories: Understanding, Deriving and Extending the LSTM Tue 26 July 2016 When I was first introduced to Long Short-Term Memory networks (LSTMs), it was hard to look past their complexity. I didn’t understand why they were designed the…

衰落信道参数包括多径扩展和多普勒扩展.时不变的多径扩展相当于一个延时抽头滤波器,而多普勒扩展要注意多普勒功率谱密度,通常使用Jakes功率谱.高斯.均匀功率谱. 多径衰落信道由单径信道叠加而成,而单径信道中最重要的就是瑞利(Rayleigh)平坦衰落信道. 下面给出瑞利平坦衰落信道的改进Jakes模型的实现: function [h]=rayleigh(fd,t) %改进的jakes模型来产生单径的平坦型瑞利衰落信道 %Yahong R.Zheng and Chengshan Xiao "Imp…

最近关注了一些Deep Learning在Information Retrieval领域的应用,得益于Deep Model在对文本的表达上展现的优势(比如RNN和CNN),我相信在IR的领域引入Deep Model也会取得很好的效果. IR的范围可能会很广,比如传统的Search Engine(query retrieves documents),Recommendation System(user retrieves items)或者Retrieval based Question Answe…

Link of the Paper: https://arxiv.org/abs/1411.4389 Main Points: A novel Recurrent Convolutional Architecture ( CNN + LSTM ): both Spatially and Temporally Deep. The recurrent long-term models are directly connected to modern visual convnet models and…

https://www.zhihu.com/question/51435499 来源:知乎著作权归作者所有. 国立台湾大学的李宏毅教授在其机器学习课程中有讲到深度神经网络的 End-to-end Learning,具体可参看其课件或课程视频的后半部分: 课件:http://speech.ee.ntu.edu.tw/~tlkagk/courses/ML_2016/Lecture/Why%20deep%20(v2).pdf 视频:https://www.youtube.com/watch?v=XsC…

[NLG - E2E - knowledge guide generation] 1. Knowledge Diffusion for Neural Dialogue Generation ( ‎Cited by 3 ) Shuman Liu, Hongshen Chen, Zhaochun Ren, Yang Feng, Qun Liu, Dawei Yin End-to-end neural dialogue generation has shown promising results re…

Emotion Recognition Using Graph Convolutional Networks 2019-10-22 09:26:56 This blog is from: https://towardsdatascience.com/emotion-recognition-using-graph-convolutional-networks-9f22f04b244e Recently, deep learning has made much progress in natural…

最近(以及预感接下来的一年)会读很多很多的paper......不如开个帖子记录一下读paper心得 AI+DB A. Pavlo et al., Self-Driving Database Engineering, in Unpublished Manuscript, 2019 写到这里啦:Self-Driving Database CDBTune: An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforc…

What features of GPUs allow them to perform computations faster than a typical CPU? GPUs have a massively parallel processing architecture consisting of thousands of smaller, more efficient cores designed to handle multiple tasks simultaneously. It u…

一.基本信息 标题:Object Constraint Language for Code Generation from Activity Models 时间:2018 出版源:Information and Software Technology 领域分类:UML;XML;OCL;活动图 二.研究背景 问题定义:如何在对象约束语言的帮助下改进UML模型的代码生成. 难点:将OCL合并到UML活动模型中 相关工作:提出了OCL表达式与UML活动图关联的元模型.实现了一个名为ActivityOC…

郑重声明:原文参见标题,如有侵权,请联系作者,将会撤销发布! 顺便安利一下同组的大佬做的SNN教程:https://spikingflow.readthedocs.io/zh_CN/latest/Tutorials.html Abstract 本文在计算能力上对脉冲神经网络模型与基于McCulloch-Pitts神经元(阈值门)和基于sigmoidal门的其他神经网络模型加以比较.特别是,研究表明,就所需神经元数量而言,脉冲神经网络的计算能力比其他神经网络模型更强.这显示了一个具体的生物学相关函…

http://handong1587.github.io/deep_learning/2015/10/09/rnn-and-lstm.html  //RNN and LSTM http://handong1587.github.io/deep_learning/2015/10/09/saliency-prediction.html //saliency Predection http://handong1587.github.io/deep_learning/2015/10/09/scene-l…

对话模型此前的研究大致有三个方向:基于规则.基于信息检索.基于机器翻译.基于规则的对话系统,顾名思义,依赖于人们周密设计的规则,对话内容限制在特定领域下,实际应用如智能客服,智能场馆预定系统.基于信息检索是指根据输入语句,在回复候选集中匹配最相近的语句作为回复,涉及到特征与排序算法的选择.优点是得到的回复通常语法正确.语义明确,但由于回复是事先存在的,因此不能很好的适应语境.还有一种思路源自机器翻译,使用神经网络encode-decode框架:将输入语句映射为向量,根据向量生成回复.需要注意的是…

Language Model estimates the probs that the sequences of words can be a sentence said by a human. Training it, we can get the embeddings of the whole vocabulary. UnConditional Language Model just assigns probs to sequences of words. That's to say, gi…

Neural Machine Translation Welcome to your first programming assignment for this week! You will build a Neural Machine Translation (NMT) model to translate human readable dates ("25th of June, 2009") into machine readable dates ("2009-06-25…

介绍   前几天,某个公众号发文质疑马蜂窝网站,认为它搬运其它网站的旅游点评,对此,马蜂窝网站迅速地做出了回应.相信大多数关注时事的群众已经了解了整个事情的经过,在这里,我们且不论这件事的是是非非,也不关心它是否是通过爬虫等其他技术手段实现的.本文将会展示一种自动生成旅游点评的技术手段.我们用到的模型为LSTM模型.   LSTM模型是深度学习中一种重要的模型,全称为Long Short-Term Memory,中文译为长短期记忆网络,是RNN家族中的重要成员,它模拟了人的大脑,具有一定的记忆功…

wesome Recurrent Neural Networks A curated list of resources dedicated to recurrent neural networks (closely related todeep learning). Maintainers -Jiwon Kim,Myungsub Choi We have pages for other topics:awesome-deep-vision,awesome-random-forest Table…

自然语言处理 (NLP)问题都是序列化的.前馈神经网络,在单次前馈中对到来数据处理,假定所有输入独立,模式丢失.循环神经网络(recurrent neural network,RNN)对时间显式建模神经网络.RNN神经元可接收其他神经元加权输入.RNN神经元可与更高层建立连接,也可与更低层建立连接.隐含活性值在同一序列相邻输入间被记忆.2006年 LSTM.语音识别.语音合成.手写连体字识别.时间序列预测.图像标题生成.端到端机器翻译. RNN由神经元和连接权值构成任意有向图.输入神经元(inp…

Improvise a Jazz Solo with an LSTM Network Welcome to your final programming assignment of this week! In this notebook, you will implement a model that uses an LSTM to generate music. You will even be able to listen to your own music at the end of th…

Character level language model - Dinosaurus land Welcome to Dinosaurus Island! 65 million years ago, dinosaurs existed, and in this assignment they are back. You are in charge of a special task. Leading biology researchers are creating new breeds of…

导读 目前采用编码器-解码器 (Encode-Decode) 结构的模型非常热门,是因为它在许多领域较其他的传统模型方法都取得了更好的结果.这种结构的模型通常将输入序列编码成一个固定长度的向量表示,对于长度较短的输入序列而言,该模型能够学习出对应合理的向量表示.然而,这种模型存在的问题在于:当输入序列非常长时,模型难以学到合理的向量表示. 在这篇博文中,我们将探索加入LSTM/RNN模型中的attention机制是如何克服传统编码器-解码器结构存在的问题的. 通过阅读这篇博文,你将会学习到: 传…

转自:http://www.jeyzhang.com/understand-attention-in-rnn.html,感谢分享! 导读 目前采用编码器-解码器 (Encode-Decode) 结构的模型非常热门,是因为它在许多领域较其他的传统模型方法都取得了更好的结果.这种结构的模型通常将输入序列编码成一个固定长度的向量表示,对于长度较短的输入序列而言,该模型能够学习出对应合理的向量表示.然而,这种模型存在的问题在于:当输入序列非常长时,模型难以学到合理的向量表示. 在这篇博文中,我们将探索加…

Sequence Models This is the fifth and final course of the deep learning specialization at Coursera which is moderated by deeplearning.ai Here are the course summary as its given on the course link: This course will teach you how to build models for n…

出处:2018 AAAI SourceCode:https://github.com/salu133445/musegan abstract: (写得不错 值得借鉴)重点阐述了生成音乐和生成图片,视频及语音的不同.首先音乐是基于时间序列的:其次音符在和弦.琶音(arpeggios).旋律.复音等规则的控制之下的:同时一首歌曲是多track的.总之不能简单堆叠音符.本文基于GAN提出了三种模型来生成音乐:jamming model, the composer model and the hybri…