The first work of this kind in a monolingual setting successfully generates two and threeword phrases with predetermined syntactic structures by decoupling the task into three phases: synthesis, decomposition, and search [4]. During the synthesis phase, a vector is constructed from some input text. This vector is decomposed into multiple output vectors that are then matched to words in the voca...

The standard recurrent neural network language model (rnnlm) generates sentences one word at a time and does not work from an explicit global sentence representation. In this work, we introduce and study an rnn-based variational autoencoder generative model that incorporates distributed latent representations of entire sentences. This factorization allows it to explicitly model holistic propert...

Traditional adversarial attacks rely upon the perturbations generated by gradients from network which are generally safeguarded gradient guided search to provide an counterpart network. In this letter, we propose a novel framework generate examples where actual image is not corrupted rather its latent space representation utilized tamper inherent structure of while maintaining perceptual qualit...

Deriving a comprehensive set of reduction rules for Feynman integrals has been long-standing challenge. In this paper, we present proposed solution to problem utilizing generating functions integrals. By establishing and solving differential equations these functions, are able derive system that effectively reduce any associated their bases. We illustrate method through various examples observe...

Endurance Time method is a time history dynamic analysis in which structures are subjected to increasing excitations. These excitations are known as endurance time excitation functions (ETEF). This study proposes a new method for generating ETEFs. In the proposed method, a new basis function for representing ETEFs is introduced. This type of ETEFs representation creates an intelligent space for...