我们也跟随Blundell et al.(2015)在MNIST上实现了它,并获得了小但一致的加速。在Penn Treebank任务中,更低的复杂度可以通过改变模型架构来实现,这应该是对我们将权重作为随机变量的工作的补充——我们只是对评估我们的方法对现有架构的影响感兴趣,而不是绝对的最先进的。值得注意的是,图2显示了权值pruning的效果:...
(b) Spatial covariance of the weights within CNN filters for a three-hidden layer network trained on MNIST, normalized by the number of channels. 图2(b)展示了CNN过滤器中的空间相关性。每个方块显示了滤波器位置(用×标记)与所有其他位置的协方差。发现较近的像素之间有很强的相关性,而较远的像素...
Experimental evaluations conducted on image classification tasks using MNIST, CIFAR-10, and CIFAR-100 datasets demonstrate the efficacy of our proposed method when applied to VGGNets and ResNets models. Results indicate a substantial energy reduction of 38.8% in VGGNets and 48.0%...
python train_Bootrap_Ensemble_MNIST.py -h Kronecker-Factorised Laplace (https://openreview.net/pdf?id=Skdvd2xAZ) Train a MAP network and then calculate a second order taylor series aproxiamtion to the curvature around a mode of the posterior. A block diagonal Hessian approximation is used, ...
First, MNIST dataset, consisting of 60K training images and 10K test images from ten handwritten digits, was collected. The gray-scale images of size 28 × 28 were observed. The convolutional neural network (ConvNet) with LeNet structure was evaluated for the estimated weights. This structure ...
The CIFAR1072 and MNIST73 datasets that we used for all our experiments are publicly available online, respectively, at https://www.cs.toronto.edu/~kriz/cifar.html and http://yann.lecun.com/exdb/mnist/. Code availability The code used to perform experiments, compute theory predictions and ...
8) in a BDAL simulation experiment based on a Modified National Institute of Standards and Technology (MNIST) dataset classification task. The results show the effectiveness and resilience of our proposed mSGLD method (Supplementary Note 5). Our proposed in situ learning algorithms leverage stochastic...
The datasets can be downloaded fromhere(1.9 GB). The folders contain preprocessed walking sequences fromCMU mocap library rotating mnist dataset generated usingthis implementation bouncing ball dataset generated usingthe codeprovided with the original paper. ...
文章非常短,不算References都不足五页,讲的是在BNN里用Leaky Relu替代Relu可以提升性能。 不过作者只在MNIST和Fashion MNIST上跑了点儿实验测了Acc、ECE,调了调Leaky Relu的超参,没搞大数据集。不知道是不是BNN研究特色?懒得仔细研究了,总之留这儿做个记录。
Our experimental results show that the network architecture can be successfully compressed by deleting parameters identified by the network itself while retaining the same level of accuracy. PDF Paper record Table 1: Storage (KB) after Compression Dataset Bayesian eVI CNN Vanilla CNN MNIST 3.25 6.25 ...