我们的目标是通过一个具有固定构型(层数、激活函数等,这样权值就是f的足够统计量)的神经网络来学习一个函数y=f(x),这为x和y之间的关系提供了一个可能的解释。权值W用贝叶斯方法建模为随机变量,并在它们上引入先验分布。由于W不是确定性的,因此神经网络的输出也是一个随机变量。通过对W的后验分布进行积分,可以...
Bayesian convolutional neural networks with bernoulli approximate variational inference. arXiv preprint arXiv:1506.02158, 2015.Gal, Y. and Ghahramani, Z. (2016b). Bayesian Con- volutional Neural Networks with Bernoulli Approxi- mate Variational Inference. ICLR Workshop Track....
下载地址:Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification 摘要: 最近,将卷积神经网络应用于图结构数据的技术已经出现。图卷积神经网络(gcnn)已被用于解决节点和图分类以及矩阵补全。尽管其性能令人印象深刻,但目前的实现在将不确定性纳入图结构方面的能力有限。几乎所有的gcnn处理图,就好...
We propose a Bayesian convolutional neural network built upon Bayes by Backprop and elaborate how this known method can serve as the fundamental construct of our novel reliable variational inference method for convolutional neural networks. First, we show how Bayes by Backprop can be applied to convo...
Bayesian Convolutional Neural Networks for Image Classification with Uncertainty Estimation To reach this goal, we have implemented a Bayesian convolutional neural network using the variational inference algorithm, Bayes by Backprop. The proposed ... F Bessai-Mechmache,MN Ghaffar,RY Laouti - 《Internat...
2. Re:卷积神经网络(Convolutional Neural Network,CNN) 非常牛逼 --xiaohuazi 3. Re:经典卷积神经网络结构——LeNet-5、AlexNet、VGG-16 博主借鉴一下leNet-5网络结构思路完成小作业写文档,跪谢! --later…… 4. Re:Adam和学习率衰减(learning rate decay) @禾禾斗斗 已修改... --wuliytTaotao 5. Re...
2. Re:卷积神经网络(Convolutional Neural Network,CNN) 非常牛逼 --xiaohuazi 3. Re:经典卷积神经网络结构——LeNet-5、AlexNet、VGG-16 博主借鉴一下leNet-5网络结构思路完成小作业写文档,跪谢! --later…… 4. Re:Adam和学习率衰减(learning rate decay) @禾禾斗斗 已修改... --wuliytTaotao 5. Re...
Notifications master 1Branch3Tags Code Folders and files Latest commit cce1dbd·Jul 4, 2020 32 Commits README MIT license BCNNs This is Chainer implementation for Bayesian Convolutional Neural Networks. (Keras and PyTorch re-impremitation are also available:keras_bayesian_unet,pytorch_bayesian_unet...
[1] Sener, Ozan, and Silvio Savarese. “Active Learning for Convolutional Neural Networks: A Core-Set Approach.” International Conference on Learning Representations, 2018. [2] Borsos, Zalán, et al. “Coresets via Bilevel Optimization for Continual Learning and Streaming.” Advances in Neural ...
Bayesian convolutional neural networks with Bernoulli approximate variational inference. CoRR abs/1506.02158 (2016). Kingma, D. P. & Ba, J. Adam: A method for stochastic optimization. arXiv:1412.6980v9 (2014). Kiureghian, A. D. & Ditlevsen, O. Aleatory or epistemic? Does it matter?