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ran
- 神经网络的资源分配网算法-Neural network resource allocation algorithm Nets
abcde
- artificial neural nets allowed merge aai
Bayes_nets_uncertainty_reasoning
- 贝叶斯网在不确定性推理中的研究 对从事这方面工作的很有指导意义-Bayes nets in the research of uncertainty reasoning in this line of work is very instructive
libORF-master
- 针对各种机器学习，深度学习领域的一个matlab工具包-A machine learning library focused on deep learning.Following algorithms and models are provided along with some static utility classes: - Naive Bayes, Linear Regression, Logistic Regression, Softmax Regression, Linear S
DeepLearning-master
- 机器学习领域中的深度学习资料，其中包括了各种语言的版本，有matlab，C语言，c++等。代码中包括了深度学习的一些模型，如栈式自动编码机，深度信念网-It s about deep learning in machine learning, including some model with different programming language. The models are stacked auto encoders, deep belief nets and so on
deepnet-master
- Nitish Srivastava University of Toronto.利用GPU训练深度学习算法-Implementation of some deep learning algorithms. Nitish Srivastava University of Toronto. GPU-based python implementation of 1. Feed-forward Neural Nets 2. Restricted Boltzmann Machines
PG_DEEP-master
- A fast learning algorithm for deep belief nets 文章代码-2006 A fast learning algorithm for deep belief nets
Sparse-Autoencoder
- 稀疏编码算法是一种无监督学习方法，它用来寻找一组“超完备”基向量来更高效地表示样本数据-2006 A fast learning algorithm for deep belief nets
code
- 卷积深度置信网，在Lee的基础上进行了一定的完善，使用RBM来预训练CNN，实现对CNN的初始化-Convolutional neural nets
dbn
- 深度置信网，经过调试，运行没有问题。运行时有点占内存，速度稍慢。-Deep Belief Nets, Restricted Boltzmann Maching
CNTK
- 在深度的重要性的驱使下，出现了一个新的问题：训练一个更好的网络是否和堆叠更多的层一样简单呢？解决这一问题的障碍便是困扰人们很久的梯度消失/梯度爆炸，这从一开始便阻碍了模型的收敛。归一初始化（normalized initialization）和中间归一化（intermediate normalization）在很大程度上解决了这一问题，它使得数十层的网络在反向传播的随机梯度下降（SGD）上能够收敛。 当深层网络能够收敛时，一个退化问题又出现了：随着网络深度的增加，准确率达到饱和（不足为奇）然后迅
dlib-master
- networking, threads, graphical interfaces, data structures, linear algebra, machine learning, XML and text parsing, numerical optimization, Bayesian nets, and numerous other tasks (Boost License)
NatureDeepReview
- 深度学习允许由多个处理层组成的计算模型来学习具有多个抽象层次的数据表示。这些方法极大地提高了语音识别、视觉对象识别、目标检测以及药物发现和基因组学等许多领域的最新进展。深度学习发现复杂的结构在大数据集，通过使用反向传播算法来指示一台机器应该如何改变其内部参数，用于计算在每一层的代表性，从上一层的代表。深层卷积网在处理图像、视频、语音和音频方面取得了突破性进展，而递归网络则在文本和语音等连续数据上起到了作用。(Deep learning allows computational models th
Learning Deep Architectures for AI
- 一本关于深度架构学习算法，尤其是用来构造更深层模型的非监督学习的单层模型。(Theoretical results suggest that in order to learn the kind of com- plicated functions that can represent high-level abstractions (e.g., in vision, language, and other AI-level tasks), one may need deep archite
RBM-DBN
- 有限玻尔兹曼机、深度置信网的Matlab实现，用mnist数据进行验证，对理解深度学习原理有帮助。(A Finite Boltzmann machine and deep belief network are implemented in MATLAB and verified with MNIST data. It is helpful to understand the principle of deep learning.)