Dynamic noisy signalling: Online appendix

Online Appendix for ``Type-Compatible Equilibria in Signalling Games''

Continuous time noisy signalling

Most real-life signalling is noisy and in many cases takes time. Information may be revealed gradually (many online customer reviews of a gadget) or by discrete events at random times (scientific breakthrough, oil spill, exposure of a corrupt politician). Both settings lead to behaviour different from noiseless or one-shot signalling situations. Signalling may occur in multiple disjoint interva...

Online Appendix for ``Learning and Type Compatibility in Signalling Games''

Appendix of High Dimensional Dynamic Stochastic Copula Models ∗

This is an on-line appendix showing some of the details of implementation. The notation used is defined in the paper.

A Convolutional Neural Network based on Adaptive Pooling for Classification of Noisy Images

Convolutional neural network is one of the effective methods for classifying images that performs learning using convolutional, pooling and fully-connected layers. All kinds of noise disrupt the operation of this network. Noise images reduce classification accuracy and increase convolutional neural network training time. Noise is an unwanted signal that destroys the original signal. Noise chang...