StatsPAI is for empirical researchers who would normally jump between Stata, R, and Python. Its goal is to make common Stata/R econometrics and causal-inference workflows feel native in Python: load a ...

Abstract: Call graphs play an important role in different contexts, such as profiling and vulnerability propagation analysis. Generating call graphs in an efficient manner can be a challenging task ...

When it comes to working with data in a tabular form, most people reach for a spreadsheet. That’s not a bad choice: Microsoft Excel and similar programs are familiar and loaded with functionality for ...

An important typo: In the current arxiv version of the manuscript, there is a description ``to verify the effectiveness of the proposed SSS metric, we also implement a naive multi-frame VPR model by ...

Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque. A popular diagnostic for understanding the decisions ...

There’s a lot to know about search intent, from using deep learning to infer search intent by classifying text and breaking down SERP titles using Natural Language Processing (NLP) techniques, to ...

The domain and IP addresses involved do not appear in any previously documented incidents, and the malware does not share any code similarities with previously known malicious software. Since this ...

PyOD is a versatile toolkit for detecting outliers in multivariate data, introduced in 2019. Outlier detection identifies data points that significantly differ from the majority, aiding in tasks like ...

Pastas is an open-source Python framework designed for processing, simulation and analysis of hydrogeological time series models. It has built-in tools for statistically analyzing, visualizing and ...