Agnostic Detection

Agnostic detection focuses on identifying anomalies or signals without relying on prior knowledge of specific classes or models. Current research explores data-driven approaches, leveraging techniques like density estimation, low-pass filtering, and efficient pooling methods to detect signals in high-dimensional spaces across diverse applications, including particle physics, video action recognition, and cybersecurity. This field is significant because it enables the detection of novel phenomena or malicious activities that may not fit existing models, improving the robustness and adaptability of detection systems in various domains.