2015. Weight uncertainty in neural networks. In Proceedings of the 32nd International Conference on International Conference on Machine Learning - Volume 37 (ICML'15). JMLR.org, 1613–1622. 摘要 我们引入了一种新的、高效的、有原则的、兼容反向传播的算法来学习神经网络权值的概率分布,称之为Bayes by...
Network Uncertainty 方向非常经典的一篇文章,同时也是贝叶斯神经网络奠基作之一, 1100+ 次引用 用Bayes衡量模型参数的不确定度 Main Idea 网络权重不再是一个单个的值,而是一个数值分布。(文中假设为高斯分布) 那么P(y|x,w)就是特定权重分布,特定输入下输出的分布。 那么网络权重需要最大化的就是 MLE。(这个可...
Weight uncertainty in neural networks. In Interna- tional Conference on Machine Learning (ICML), pages 1613-1622, 2015. (Cited on page 18.)Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra. Weight uncertainty in neural networks. International Conference on Machine Learning...
WeightUncertaintyinNeural Networks CharlesBlundell,JulienCornebise,KorayKavukcuoglu, DaanWierstra PresentedbyMichaelCogswell PointEstimatesofNetworkWeights MLE PointEstimatesofNeuralNetworks MAP ADistributionoverNeuralNetworks IdealTestDistribution Approximate
Hyperspherical Weight Uncertainty in Neural Networks Bayesian neural networks learn a posterior probability distribution over the weights of the network to estimate the uncertainty in predictions. Parameteriz... B Ghoshal,A Tucker 被引量: 0发表: 2021年 Training Reformulated Radial Basis Function Neural ...
Neural activity in the human brain relating to uncertainty and arousal during anticipation. Neuron. 2001;29(2):537-54511239442PubMedGoogle ScholarCrossref 69. Talairach J, Tournous J. Co-planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System—An Approach to Cerebral ...
Surrogate model development is a critical step for uncertainty quantification or other sample-intensive tasks for complex computational models. In this work we develop a multi-output surrogate form using a class of neural networks (NNs) that employ shortcut connections, namely Residual NNs (ResNets)...
Zhang Y, Wang C, Deng W (2021) Relative uncertainty learning for facial expression recognition. Adv Neural Inform Process Syst 34:17616–17627 MATH Google Scholar Nan Y, Ju J, Hua Q, Zhang H, Wang B (2022) A-MobileNet: an approach for facial expression recognition. Alex Eng J 61:4435...
18 proposed a data-driven approach to quantify the prediction uncertainty of deep neural networks (DNNs), paving the way for a comprehensive treatment of uncertainty in DNN-based diagnostic systems. Saxena et al.19 applied an advanced convolutional neural network model for early detection of DR to...
with the underlying idea to maximize the weight diversity. Under this paradigm, the epistemic uncertainty is described by the weight distribution of maximal entropy that produces neural networks "consistent" with the training observations. Considering stochastic neural networks, a practical optimization is...