This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

Data-driven AI systems increasingly influence our choices, raising concerns about autonomy, fairness, and accountability. Achieving algorithmic autonomy requires new infrastructures, motivation ...

This repository contains the implementation of topological data analysis (TDA) methods for detecting adversarial examples in deep learning models, particularly focusing on Vision-Language models like ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

Wrapping up a multi-week series on Crafting Data Personas. What are they, why are they important, and how to get started. Continuing from last week, we’re diving right into examples of personas. I ...

ABSTRACT: Mental disorders, including depression, bipolar disorder, and mood disorders, affect millions of individuals worldwide, significantly impacting their quality of life. Early and accurate ...

For lithologic oil reservoirs, lithology identification plays a significant guiding role in exploration targeting, reservoir evaluation, well network adjustment and optimization, and the establishment ...

During the model training process (I am referring to the process that includes generating synthetic data and involves backpropagation), when preprocessing features, the training samples are used to ...

The world as we know it has been transformed by AI, but perhaps no field has been more profoundly affected than analytics and data science. While traditional data science practices have paved the way ...