Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: A Practical Bayesian Framework for Backprop Networks
learning representations by back - propagating errors .
A Tutorial on Learning With Bayesian Networks
Learning Probabilistic Networks
Neural Networks: Tricks of the Trade
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
Learning Gaussian Networks
A Bayesian Perspective on Generalization and Stochastic Gradient Descent
Pipelined BackPropagation for Context-Dependent Deep Neural Networks
ZhuSuan: A Library for Bayesian Deep Learning
Applications of counterpropagation networks
Deriving optimal weights in deep neural networks
Finding Optimal Bayesian Networks
backpropagation : past and future .
On the Computational Efficiency of Training Neural Networks
Training Binary Multilayer Neural Networks for Image Classification using Expectation Backpropagation
Bayesian Learning via Stochastic Gradient Langevin Dynamics
A Gentle Tutorial of Recurrent Neural Network with Error Backpropagation
Backpropagation for Implicit Spectral Densities
Neural Network Classifiers Estimate Bayesian a posteriori Probabilities
VisualBackProp for learning using privileged information with CNNs
ViBE: A powerful random technique to estimate the background in video sequences
Learning object repositories as knowledge management systems
On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
Novel Speed-Bump Design and Optimization for Energy Harvesting From Traffic
Designing simple nonlinear filters using hysteresis of single recurrent neurons for acoustic signal recognition in robots