4 citations · 10 across the 7 of their papers we have counts for
9 papers
Sparks in the Dark
Olga Sunneborn Gudnadottir, Axel Gallén, Giulia Ripellino +3
This study presents a novel method for the definition of signal regions in searches for new physics at collider experiments, specifically those conducted at CERNs Large Hadron Coll…
Detecting Slag Formations with Deep Convolutional Neural Networks
Christian von Koch, William Anzén, Max Fischer +1
We investigate the ability to detect slag formations in images from inside a Grate-Kiln system furnace with two deep convolutional neural networks. The conditions inside the furnac…
Distributed training and scalability for the particle clustering method UCluster
Olga Sunneborn Gudnadottir, Daniel Gedon, Colin Desmarais +3
In recent years, machine-learning methods have become increasingly important for the experiments at the Large Hadron Collider (LHC). They are utilised in everything from trigger sy…
Scalable Multivariate Histograms
Raazesh Sainudiin, Warwick Tucker, Tilo Wiklund
We give a distributed variant of an adaptive histogram estimation procedure previously developed by the first author. The procedure is based on regular pavings and is known to have…
Some Distributions on Finite Rooted Binary Trees
Sean Cleary, Mareike Fischer, Robert C. Griffiths +1
We introduce some natural families of distributions on rooted binary ranked plane trees with a view toward unifying ideas from various fields, including macroevolution, epidemiolog…
A Beta-splitting model for evolutionary trees
Raazesh Sainudiin, Amandine Veber
In this article, we construct a generalization of the Blum-François Beta-splitting model for evolutionary trees, which was itself inspired by Aldous' Beta-splitting model on cladog…