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Found 6 papers, 1 papers with code
Spherical Poisson Point Process Intensity Function Modeling and Estimation with Measure Transport
Recent years have seen an increased interest in the application of methods and techniques commonly associated with machine learning and artificial intelligence to spatial statistics.
Fact Check: Analyzing Financial Events from Multilingual News Sources
The explosion in the sheer magnitude and complexity of financial news data in recent years makes it increasingly challenging for investment analysts to extract valuable insights and perform analysis.
Posterior Regularization on Bayesian Hierarchical Mixture Clustering
Bayesian hierarchical mixture clustering (BHMC) improves traditionalBayesian hierarchical clustering by replacing conventional Gaussian-to-Gaussian kernels with a Hierarchical Dirichlet Process Mixture Model(HDPMM) for parent-to-child diffusion in the generative process.
Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification
Corporate mergers and acquisitions (M&A) account for billions of dollars of investment globally every year, and offer an interesting and challenging domain for artificial intelligence.
Deep Compositional Spatial Models
Spatial processes with nonstationary and anisotropic covariance structure are often used when modelling, analysing and predicting complex environmental phenomena.
