Abstract: We propose a general attack framework based on evolutionary algorithms to quickly and efficiently generate low-perturbation adversarial samples for 3D point cloud data. Specifically, we ...

polars-bloomberg is a Python library that extracts Bloomberg's financial data directly into Polars DataFrames. If you’re a quant financial analyst, data scientist, or quant developer working in ...

A powerful and intuitive Python library for exploratory data analysis and data profiling. Pydata-visualizer automatically analyzes your dataset, generates interactive visualizations, and provides ...

Abstract: In recent years, surrogate-assisted evolutionary algorithms (SAEAs) have been extensively utilized to address expensive optimization problems. However, it becomes a great challenge how to ...