Abstract: Circuit prototype debug can be challenging for students and novice engineers for which emerging intelligent Bayesian statistical methods have potential application. We introduce an automated ...

In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing ...

A lot of money has been spent on data center infrastructure that's optimized to train models using large datasets. Inference, on the other hand, doesn't require as much parallel-processing power as ...

StatsPAI is the agent-native Python package for causal inference and applied econometrics. One import, 800+ functions, covering the complete empirical research workflow — from classical econometrics ...

Empirical investigation requires dealing with fundamental uncertainty. In experimental psychology, research questions are often addressed using Null Hypothesis Significance Testing (NHST), an approach ...

Industry groups and drugmakers want the US Food and Drug Administration (FDA) to explicitly clarify that Bayesian statistical methods can be used for products beyond those intended for children and ...

Ultimately, the stock best positioned to win is likely ASML (ASML +9.76%). Admittedly, that may come as a surprise, particularly because the company bills itself as the "most important company you've ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Birgitta Böckeler, Distinguished Engineer at ...

A production-grade Python package for modeling financial time series using Bayesian jump-diffusion processes. This package implements 9 advanced models, comprehensive risk metrics, portfolio ...