Variational auto-encoders (VAE) are scalable and powerful generative models. However, the choice of the variational posterior determines tractability and flexibility of the VAE. Commonly, latent variables are modeled using the normal distribution with a diagonal covariance matrix. This results in computational efficiency but typically it is not flexible enough to match the true posterior distri...

In this article, we propose a method to estimate the synthetic aperture radar interferometry (InSAR) interferometric phase based on the model of correlation weight joint pixel by using the joint subspace projection technique. In the method, the correlation weight joint data vector is constructed and the data vector can make the noise subspace dimension of the corresponding weight covariance mat...

Auto Tutor is an intelligent tutoring system that holds conversations with learners in natural language. Auto Tutor uses Latent Semantic Analysis (LSA) to match sentences the student generates in response to essay type questions to a set of sentences (expectations) that would appear in a complete and correct response or which reflect common but incorrect understandings of the material (bads). T...

Motivated by the growing importance of social media, this paper examines the relationship between new media, old media, and sales, in the context of the music industry. In particular, we study the interplay between blog buzz, radio play and music sales, at both the album and song levels of analysis. We employ the Panel Vector Auto-regression (PVAR) methodology, an extension of vector auto-regre...

 In this paper, a version of the Vector Auto Regression (VAR) model has been used to investigate the interacted and dynamic effects between social capital and economic development in Iran during the period 1987-2006. To this purpose, variables of human capital, health and income distribution have been considered as the proxies of economic development. In addition, the volume of risky bank chequ...

The purpose of this study is to investigate the impact of exchange rate misalignment on inflation persistence. For this purpose, Vector Auto Regression method and Markov Switching model is used for quarterly data during 1989:4 -2014:3. The results show that, the impact of liquidity growth and exchange rate misalignment on inflation persistence is positive. On the other hand, GDP growth has a ne...

This paper tries to analyze effects of trade and financial liberalizations on the Iran’s government size during both long-run and short- run. Accordingly, a specification of the auto regression with distributed lag (ARDL) has been used for investigating the long run relationships between variables, and a vector correction model (VECM) has examined dynamically the short-run relationships betwe...

A central problem ill empirical macroeconomics is to determine when and how much the exchange rate is misaligned. This paper clarifies and calculates the concept of’ the equilibrium real exchange rate, using a structural vector auto regression (VAR) model. By imposing long—run restrictions on a VAR model for Iran, lour structural shocks are identified: nominal demand, real demand, supply and oi...