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Generative adversarial networks are a kind of artificial intelligence algorithm designed to solve the generative modeling problem. The goal of a generative model is to study a collection of training examples and learn th...

Subjects / keywords: Discriminator; Generator (circuit theory); Generative grammar; Adversarial system; Set (abstract data type); Computer science; Artificial intelligence; Artificial neural network; Order (exchange); Machine learning; Econo...

Despite the breakthroughs in accuracy and speed of single image super-resolution using faster and deeper convolutional neural networks, one central problem remains largely unsolved: how do we recover the finer texture de...

We propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two models: a generative model G that captures the data distribution, and a discriminative model D ...

La inteligencia artificial permite la innovación y el cambio en todos los aspectos de la vida moderna. La mayoría de los avances actuales se basan en Deep Learning, un área de conocimiento muy madura que permite a las...

Are the copyright and authors’ rights systems truly that different? Why is the model of copyright protection within the European Union globally relevant? Should access to cultural heritage assets or open science ...

Le presentamos el primer libro escrito en español sobre Autodesk Fusion 360. Fusion 360 es una herramienta de CAD, CAM y CAE con prestaciones profesionales y licencia gratuita para uso personal o startups desarrollada p...

Automático (Machine Learning). El objetivo del machine learning es que los sistemas informáticos sean capaces de aprender a partir de los datos, emulando de esta manera las capacidades humanas. El Aprendizaje Profundo ...

Ist die altportugiesische Wortstellung freier als die des modernen Portugiesischen? Inwieweit zeigen sich in den frühesten portugiesischen Texten noch Einflüsse des Lateinischen? Ziel dieses Buches ist, die Wortstellun...

A first step in identifying the content of a document is determining which topics that document addresses. We describe a generative model for documents, introduced by Blei, Ng, and Jordan [Blei, D. M., Ng, A. Y. & Jordan...

We show how to use "complementary priors" to eliminate the explaining-away effects that make inference difficult in densely connected belief nets that have many hidden layers. Using complementary priors, we derive a fast...

Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to useful intermediate representations. We intr...

We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection ...

The emerging field of emotion regulation studies how individuals influence which emotions they have, when they have them, and how they experience and express them. This review takes an evolutionary perspective and charac...

A classic work that situates linguistic theory in the broader cognitive sciences, formulating and developing the minimalist program. In his foundational book, The Minimalist Program, published in 1995, Noam Chomsky offer...

Subjects / keywords: automated texts, generative ai, romance languages, linguistics, texts and discourses, germanic languages; Language and Literature: Philology. Linguistics: Computational linguistics. Natural language processing

Subjects / keywords: artificial intelligence, machine learning, large language models, generative ai, deep learning, artificial neural networks; Science: Mathematics: Instruments and machines: Electronic computers. Computer science; Technolo...

Subjects / keywords: metaverse, artificial intelligence, generative ai, virtual reality, augmented reality, virtual worlds; Technology