Here we propose a method to build a set of linearly independent vectors in the latent space of a trained GAN, which we call quasi-eigenvectors. These quasi-eigenvectors have two key properties: i) They span the latent space, ii) A set of these quasi-eigenvect...
Advised by our domain experts, who are long-time Chinese music performers, we know in order to differentiate or compare the semantic meaning of music segments, the duration of a music segment needs to be at least 10 s. Due to the fact that the sampling rate for the original spectrogram is...
The latent space has no meaning other than the meaning applied to it via the generative model. Yet, the latent space has structure that can be explored, such as by interpolating between points and performing vector arithmetic between points in latent space which have meanin...
On the other hand, when used in latent space its meaning is different. For instance, 6. Implementation an image translation by a pixel could lead to a large dis- crepancy in image space, while in latent space its represen- Adversarial losses and regularization. We use a non- tation would...
Searching for relevant knowledge with a semantic meaning consists mostly in visual human inspection of the data, regardless of the application. The method presented in this paper is an innovation in the field of information retrieval. It aims to discover latent semantic classes containing pairs of ...
Visualization and Analysis of Frames in Collections of Messages: Content Analysis and the Measurement of Meaning We distinguish between the communication of information in the network space (social network analysis) and the communication of meaning in the vector space... E Vlieger,L Leydesdorff - IGI...
Although the meaning oflatentis “existing but not yet manifest”,latent spaceis dependent on the context in which the term is used in different domains. Latent space generally refers to a space that is not tangible but is inferred or explored from the observed data. However, in machine learn...
This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individ...
A Chinese text classification model based on vector space and semantic meaning Aiming at the status that various electronic text materials are increasing rapidly, This work brings forward a model of automatic classification of electro... BY Wang,SM Zhang - International Conference on Machine Learning...
protein sequences in a manner that requires no labeling information. Through this combination of statistical models, we create a latent generative landscape (LGL), where accessible VAE sequence space is assessed using the inferred fitness from DCA. By exploring a large amount of sequence space, we...