The advent of big data has transformed the landscape of statistical science, demanding methods that can handle unprecedented volume, velocity and variety. Traditional inference techniques, designed ...

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 Bayesian particle Gibbs framework enables unbiased spike time inference with millisecond resolution and jointly estimates uncertainties in both spike timing and model parameters from fast calcium ...

DTSA 5001 Probability and Foundations for Data Science and AI - Same as APPA 5001 DTSA 5002 Statistical Estimation for Data Science and AI - Same as APPA 5003 DTSA 5003 Statistical Inference and ...

Enterprises racing to deploy generative AI often focus on models. In practice, outcomes depend on how well organizations prepare, manage, and move their data. AI-ready data platforms, vector databases ...

In the 21st century, artificial intelligence (AI) has emerged as a valuable approach in data science and a growing influence in medical research, 4-6 with an accelerating pace of innovation. This ...

You train the model once, but you run it every day. Making sure your model has business context and guardrails to guarantee reliability is more valuable than fussing over LLMs. We’re years into the ...