$ν^2$-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows

1 code implementation • 5 Jul 2023 • John Andrew Raine, Matthew Leigh, Knut Zoch, Tobias Golling

In this work we introduce $\nu^2$-Flows, an extension of the $\nu$-Flows method to final states containing multiple neutrinos.

Topological Reconstruction of Particle Physics Processes using Graph Neural Networks

1 code implementation • 24 Mar 2023 • Lukas Ehrke, John Andrew Raine, Knut Zoch, Manuel Guth, Tobias Golling

We present a new approach, the Topograph, which reconstructs underlying physics processes, including the intermediary particles, by leveraging underlying priors from the nature of particle physics decays and the flexibility of message passing graph neural networks.

PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics

1 code implementation • 9 Mar 2023 • Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant, John Andrew Raine, Knut Zoch, Tobias Golling

In this paper, we present a new method to efficiently generate jets in High Energy Physics called PC-JeDi.

Vocal Bursts Intensity Prediction