22 citations · 49 across the 3 of their papers we have counts for
10 papers
Quantum-inspired event reconstruction with Tensor Networks: Matrix Product States
Jack Y. Araz, Michael Spannowsky
Tensor Networks are non-trivial representations of high-dimensional tensors, originally designed to describe quantum many-body systems. We show that Tensor Networks are ideal vehic…
Elvet -- a neural network-based differential equation and variational problem solver
Jack Y. Araz, Juan Carlos Criado, Michael Spannowsky
We present Elvet, a Python package for solving differential equations and variational problems using machine learning methods. Elvet can deal with any system of coupled ordinary or…
Combine and Conquer: Event Reconstruction with Bayesian Ensemble Neural Networks
Jack Y. Araz, Michael Spannowsky
Ensemble learning is a technique where multiple component learners are combined through a protocol. We propose an Ensemble Neural Network (ENN) that uses the combined latent-featur…
Proceedings of the second MadAnalysis 5 workshop on LHC recasting in Korea
Benjamin Fuks, Pyungwon Ko, Seung J. Lee +32
We document the activities performed during the second MadAnalysis 5 workshop on LHC recasting, that was organised in KIAS (Seoul, Korea) on February 12-20, 2020. We detail the imp…
Precision SMEFT bounds from the VBF Higgs at high transverse momentum
Jack Y. Araz, Shankha Banerjee, Rick S. Gupta +1
We study the production of Higgs bosons at high transverse momenta via vector-boson fusion (VBF) in the Standard Model Effective Field Theory (SMEFT). We find that contributions fr…
Simplified fast detector simulation in MadAnalysis 5
Jack Y. Araz, Benjamin Fuks, Georgios Polykratis
We introduce a new simplified fast detector simulator in the MadAnalysis 5 platform. The Python-like interpreter of the programme has been augmented by new commands allowing for a…