编程语言,算法相关技术专家
Dissecting Reinforcement Learning-Part.2 Jan 15, 2017 • Massimiliano Patacchiola 原文链接:https://mpatacchiola.
本文转自: http://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==&mid=2650722318&idx=4&sn=728e8e264ca05f2366d75a27744bb383&chksm=871b1470b06c9d669f9a077f0b41502d...
>>> import caffeTraceback (most recent call last): File "", line 1, in File "/home/wangxiao/Downloads/project/caffe-master/python/caffe/__init__.
本文转自:http://www.metamorphosite.com/one-way-hash-encryption-sha1-data-software Home Posted: November 12, 2007 How Hash Algorithms Work This page ...
深度学习 目标检测算法 SSD 论文简介 一、论文简介: ECCV-2016 Paper:https://arxiv.org/pdf/1512.02325v5.pdf Slides:http://www.
本文转自:https://github.com/betars/Face-Resources Face-Resources Following is a growing list of some of the materials I found on the web for research on face recognition algorithm.
本文转自:https://github.com/zhangqianhui/AdversarialNetsPapers AdversarialNetsPapers The classical Papers about adversarial nets The First pap...
本文转自:http://www.jianshu.com/p/2acb804dd811 GAN论文整理 作者 FinlayLiu 已关注 2016.11.09 13:21 字数 1551 阅读 1263评论 0喜欢 7 原始GAN Goodfellow和Bengio等人发表在NIPS 2014年的文章Generative adversary network,是生成对抗网络的开创文章,论文思想启发自博弈论中的二人零和博弈。
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks 本文将利用 GANs 进行高质量图像生成,分为两个阶段进行,coarse to fine 的过程。
转自:http://www.jeremydjacksonphd.com/category/deep-learning/ Deep Learning Resources Posted on May 13, 2015 Videos Deep Learning and Neur...
转自:https://blog.infermedica.com/three-challenges-youre-going-to-face-when-building-a-chatbot/ Three challenges you’re going to face when building a chatbot Adam Radziszewski on Dec.
转自:http://blog.evjang.com/2017/01/nips2016.html Eric Jang Technology, A.I., Careers M...
转自:http://www.asimovinstitute.org/neural-network-zoo/ THE NEURAL NETWORK ZOO POSTED ON SEPTEMBER 14, 2016 BY FJODOR VAN VEEN With ne...
Attribute2Image --- Conditional Image Generation from Visual Attributes Target: 本文提出一种根据属性生成图像的产生式模型 。
LSTM NEURAL NETWORK FOR TIME SERIES PREDICTION Wed 21st Dec 2016 Neural Networks these days are the “go to” thing when talking about new fads in machine learning.
Conditional Variational Autoencoders --- 条件式变换自编码机 Goal of a Variational Autoencoder: 一个 VAE(variational autoencoder)是一个产生式模型,意味着我们可以产生看起来像我们的训练数据的 samples。
About Contact Subscribe Back-propagation, an introduction Sanjeev Arora and Tengyu Ma • Dec 20, 2016 • 20 minute read Given the sheer n...
Torch 网络层 参数的初始化问题 参考链接: https://github.com/Kaixhin/nninit 从 Torch 中自带的包,可以看到:https://github.
Torch 7 load saved model failed, 加载保存的模型失败: 可以尝试下面的解决方案:
Daniil's blog Machine Learning and Computer Vision artisan. About/ Blog/ Image Segmentation with Tensorflow using CNNs and Conditional Random ...
这两天装 Linux 系统,总是遇到一个很蛋疼的问题: 当你累死累活把分区什么的都设置好了之后,在输入了系统名字,开机密码那几项之后,再选择地点的时候(如:选择 “上海”),然后就会卡死,然后,闪退到,刚开始进去安装镜像的那个界面,怎么回事呢? --- 答曰:万恶的Linux,万恶的网线! 将网线拔掉(即:装Linux时,千万不要联网)。
Awesome Deep Learning Table of Contents Free Online Books Courses Videos and Lectures Papers Tutorials Researchers WebSites Dataset...
1. http://www.machinedlearnings.com/2016/12/nips-2016-reflections.html 2. http://blog.arpitmohan.
Playing FPS games with deep reinforcement learning 博文转自:https://blog.acolyer.org/2016/11/23/playing-fps-games-with-deep-reinforcement-learning/ ...
How to Train a GAN? Tips and tricks to make GANs work 转自:https://github.com/soumith/ganhacks While research in Generative Adversarial Networks (G...
The major advancements in Deep Learning in 2016 Pablo Tue, Dec 6, 2016 in MACHINE LEARNING DEEP LEARNING GAN Deep Learning has been the core top...
Artificial intelligence, revealed Yann LeCunJoaquin Quiñonero Candela It’s 8:00 am on a Tuesday morning.
Predictive learning vs. representation learning 预测学习 与 表示学习 When you take a machine learning class, there’s a good chance it’s divided into a un...
Lua 调用 Opencv 的方法 最近想用 Lua 调用 Opencv 进行相关像素级操作,如:bitwise_and 或者 bitwise_or,从而完成图像 IoU 的计算。 那么,怎么用 Lua 调用 Opencv 呢? 查了 Torch 的官方文档,发现只有这么几个可以调用的包: 链接: https://github.
Torch 日志文件的保存 logroll 怎样将 Torch 在终端显示的信息,保存到 log 文件中 ? 现在介绍一种方法:利用 logroll 的方式。 参考 https://github.
Deep Reinforcement Learning Papers A list of recent papers regarding deep reinforcement learning.
Andrej Karpathy blog About Hacker's guide to Neural Networks A Survival Guide to a PhD Sep 7, 2016 This guide is patterned after my “Doing well ...
WTF is computer vision? Posted Nov 13, 2016 by Devin Coldewey, Contributor Next Story Someone across the room throws you a ball and you catch it.
Deep Learning Research Review Week 2: Reinforcement Learning 转载自: https://adeshpande3.github.io/adeshpande3.
变分自编码器(Variational Autoencoder, VAE)通俗教程 转载自: http://www.dengfanxin.cn/?p=334&sukey=72885186ae5c357d85d72afd35935fd5253f8a4e53d4ad672d5321379584a6b6e02e9713966e5f908dd7020bfa0c555f dengfanxin 未来 2016年11月15日 1. 神秘变量与数据集 现在有一个数据集DX(dataset, 也可以叫datapoints),每个数据也称为数据点。
简述生成式对抗网络 【转载请注明出处】chenrudan.github.io 本文主要阐述了对生成式对抗网络的理解,首先谈到了什么是对抗样本,以及它与对抗网络的关系,然后解释了对抗网络的每个组成部分,再结合算法流程和代码实现来解释具体是如何实现并执行这个算法的,最后给出一个基于对抗网络改写的去噪网络运行的结果,效果虽然挺差的,但是有些地方还是挺有意思的。
Hierarchical Object Detection with Deep Reinforcement Learning NIPS 2016 WorkShop Paper : https://arxiv.
Speed Up Tracking by Ignoring Features CVPR 2014 Abstract:本文提出一种特征选择的算法,来实现用最“精简”的特征以进行目标跟踪。重点是提出一种上界 (Upper Bound)来表示一块区域包含目标物体的概率,并且忽略掉这个 bound比较小的区域。
深度学习中常见的几个基础概念 1. Linear regression : Linear regression 对监督学习问题来说, 是最简单的建模形式. 上图蓝色点表示 training data point, 红色的线表示用于拟合训练数据的线性函数.
The AlphaGo Replication Wiki 摘自:https://github.com/Rochester-NRT/RocAlphaGo/wiki/01.-Home Contents : Home 01.
Co-saliency Detection via A Self-paced Multiple-instance Learning Framework T-PAMI 2016 摘要:Co-saliency detection 从一组图像中提取出共同显著的物体。
CVPR 2016 Visual Tracking Paper Review 本文摘自:http://blog.csdn.net/ben_ben_niao/article/details/52072659 http://blog.csdn.net/ben_ben_niao/article/details/52078727 做了一段时间的跟踪,最近CVPR大会也过了一段时间了,这次将CVPR2016跟踪的文章做一次总结,主要是对paper的方法,创新,改进等方面进行介绍和总结。
Generative Adversarial Text to Image Synthesis ICML 2016 摘要:本文将文本和图像练习起来,根据文本生成图像,结合 CNN 和 GAN 来有效的进行无监督学习。
Conditional Generative Adversarial Nets arXiv 2014 本文是 GANs 的拓展,在产生 和 判别时,考虑到额外的条件 y,以进行更加“激烈”的对抗,从而达到更好的结果。
Progressive Neural Network Google DeepMind 摘要:学习去解决任务的复杂序列 --- 结合 transfer (迁移),并且避免 catastrophic forgetting (灾难性遗忘) --- 对于达到 human-level intelligence 仍然是一个关键性的难题。
Let’s make a DQN 系列 Let’s make a DQN: Theory September 27, 2016DQN This article is part of series Let’s make a DQN.
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network 2016.10.23 摘要:本文针对传统超分辨方法中存在的结果过于平滑的问题,提出了结合最新的对抗网络的方法,得到了不错的效果。
一张图解AlphaGo原理及弱点 2016-03-23 郑宇,张钧波 CKDD 作者简介: 郑宇,博士, Editor-in-Chief of ACM Transactions on Intelligent Systems and Technology, ACM数据挖掘中国分会秘书长。
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks NIPS 2015 摘要:本文提出一种 generative parametric model 能够产生高质量自然图像。
注意力机制(Attention Mechanism)在自然语言处理中的应用 本文转自:http://www.cnblogs.com/robert-dlut/p/5952032.html 近年来,深度学习的研究越来越深入,在各个领域也都获得了不少突破性的进展。