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Found 9 papers, 2 papers with code
KG-FRUS: a Novel Graph-based Dataset of 127 Years of US Diplomatic Relations
In the current paper, we present the KG-FRUS dataset, comprised of more than 300, 000 US government diplomatic documents encoded in a Knowledge Graph (KG).
Regularizing Transformers With Deep Probabilistic Layers
Language models (LM) have grown with non-stop in the last decade, from sequence-to-sequence architectures to the state-of-the-art and utter attention-based Transformers.
Robust Sampling in Deep Learning
Deep learning requires regularization mechanisms to reduce overfitting and improve generalization.
Complex-Valued Kernel Methods for Regression
Usually, complex-valued RKHS are presented as an straightforward application of the real-valued case.
Gaussian Processes for Nonlinear Signal Processing
Gaussian processes (GPs) are versatile tools that have been successfully employed to solve nonlinear estimation problems in machine learning, but that are rarely used in signal processing.
Bayesian Nonparametric Modeling of Suicide Attempts
In the present paper, we are interested in seeking the hidden causes behind the suicide attempts, for which we propose to model the subjects using a nonparametric latent model based on the Indian Buffet Process (IBP).
An Application of Tree-Structured Expectation Propagation for Channel Decoding
We show an application of a tree structure for approximate inference in graphical models using the expectation propagation algorithm.
Estimation of Information Theoretic Measures for Continuous Random Variables
We analyze the estimation of information theoretic measures of continuous random variables such as: differential entropy, mutual information or Kullback-Leibler divergence.
