no code implementations • 15 Feb 2021 • Purvasha Chakravarti, Mikael Kuusela, Jing Lei, Larry Wasserman
Here we instead investigate a model-independent method that does not make any assumptions about the signal and uses a semi-supervised classifier to detect the presence of the signal in the experimental data.
Applications High Energy Physics - Phenomenology Data Analysis, Statistics and Probability
no code implementations • 7 Oct 2019 • Purvasha Chakravarti, Sivaraman Balakrishnan, Larry Wasserman
We consider clustering based on significance tests for Gaussian Mixture Models (GMMs).
1 code implementation • 26 Apr 2017 • Yotam Hechtlinger, Purvasha Chakravarti, Jining Qin
This paper introduces a generalization of Convolutional Neural Networks (CNNs) from low-dimensional grid data, such as images, to graph-structured data.