Distributional regression for seasonal data: an application to river flows (Perreault, Pesenti, Shahzad) Risk assessment in casualty insurance, such as flood risk, traditionally relies on extreme-value methods that emphasizes rare events. These approaches are well-suited for characterizin
Distributional regression for seasonal data: an application to river flows (Perreault, Pesenti, Shahzad) Risk assessment in casualty insurance, such as flood risk, traditionally relies on extreme-value methods that emphasizes rare events. These approaches are well-suited for characterizin
Differentially Private E-Values (Csillag, Mesquita) E-values have gained prominence as flexible tools for statistical inference and risk control, enabling anytime- and post-hoc-valid procedures under minimal assumptions. However, many real-world applications fundamentally rely on sensitiv
Differentially Private E-Values (Csillag, Mesquita) E-values have gained prominence as flexible tools for statistical inference and risk control, enabling anytime- and post-hoc-valid procedures under minimal assumptions. However, many real-world applications fundamentally rely on sensitiv
A Frequentist Statistical Introduction to Variational Inference, Autoencoders, and Diffusion Models (Chen) While Variational Inference (VI) is central to modern generative models like Variational Autoencoders (VAEs) and Denoising Diffusion Models (DDMs), its pedagogical treatment is split
A Frequentist Statistical Introduction to Variational Inference, Autoencoders, and Diffusion Models (Chen) While Variational Inference (VI) is central to modern generative models like Variational Autoencoders (VAEs) and Denoising Diffusion Models (DDMs), its pedagogical treatment is split
A model-free subdata selection method for classification () arXiv:2404.19127v1 Announce Type: new
Abstract: Subdata selection is a study of methods that select a small representative sample of the big data, the analysis of which is fast and statistically efficient. The existing subdata s
A model-free subdata selection method for classification () arXiv:2404.19127v1 Announce Type: new
Abstract: Subdata selection is a study of methods that select a small representative sample of the big data, the analysis of which is fast and statistically efficient. The existing subdata s
SUJEITO À PAULADA
SUJEITO À PAULADA
00h00 - sou um pobre empreendedor não posso dar 2 dias de folga pra meus empregados.
Muitas camadas. 😂
Muitas camadas. 😂