activity
20172025
most citedOBOE: Collaborative Filtering for AutoML Model Selection

90 citations · 181 across the 10 of their papers we have counts for

collaborators

11 papers

physics.flu-dyn2025

Measuring the effect of spatial dimension on hydrodynamic turbulence using direct numerical simulation

Richard D. J. G. Ho, Daniel Clark, Andres Armua +3

We perform direct numerical simulation of the incompressible Navier-Stokes equation with forcing at different spatial dimensions and measure turbulent and chaotic properties. Lyapu…

physics.flu-dyn2024

Chaotic measures as an alternative to spectral measures for analysing turbulent flow

Richard D. J. G. Ho, Daniel Clark, Arjun Berera

Turbulence has associated chaotic features. In the past couple of decades there has been growing interest in the study of these features as an alternative means of understanding tu…

physics.flu-dyn2021

Critical transition to a non-chaotic regime in isotropic turbulence

Daniel Clark, Andres Armua, Richard DJG Ho +1

We study the properties of homogeneous and isotropic turbulence in higher spatial dimensions through the lens of chaos and predictability using numerical simulations. We employ bot…

physics.flu-dyn2020

Homogeneous isotropic turbulence in four spatial dimensions

Arjun Berera, Richard D. J. G. Ho, Daniel Clark

Direct Numerical Simulation is performed of the forced Navier-Stokes equation in four spatial dimensions. Well equilibrated, long time runs at sufficient resolution were obtained t…

physics.flu-dyn2020★ 12 cited

Effect of spatial dimension on a model of fluid turbulence

Daniel Clark, Richard Ho, Arjun Berera

A numerical study of the -dimensional Eddy Damped Quasi-Normal Markovian equations is performed to investigate the dependence on spatial dimension of homogeneous isotropic fluid…

physics.flu-dyn2019★ 10 cited

Fluctuations of Lyapunov Exponents in homogeneous and isotropic turbulence

Richard Ho, Andres Armua, Arjun Berera

In the context of the analysis of the chaotic properties of homogeneous and isotropic turbulence, direct numerical simulations are used to study the fluctuations of the finite time…

nlin.CD2019

High dimensional chaotic systems which behave like random walks in state space

Richard D. J. G. Ho

By analysing an n-dimensional generalisation of Thomas's cyclically symmetric attractor we find that this chaotic dynamical system behaves like a random walk constrained onto the s…

physics.flu-dyn2019★ 12 cited

Superfast amplification and superfast nonlinear saturation of perturbations as the mechanism of turbulence

Y. Charles Li, Richard D. J. G. Ho, Arjun Berera +1

Ruelle predicted that the maximal amplification of perturbations in homogeneous isotropic turbulence is exponential (where is the maximal Liapunov e…

cs.LG2018★ 90 cited

OBOE: Collaborative Filtering for AutoML Model Selection

Chengrun Yang, Yuji Akimoto, Dae Won Kim +1

Algorithm selection and hyperparameter tuning remain two of the most challenging tasks in machine learning. Automated machine learning (AutoML) seeks to automate these tasks to ena…

physics.flu-dyn2018★ 4 cited

Fully resolved array of simulations investigating the influence of the magnetic Prandtl number on magnetohydrodynamic turbulence

Mairi E. McKay, Arjun Berera, Richard D. J. G. Ho

We explore the effect of the magnetic Prandtl number Pm on energy and dissipation in fully resolved direct numerical simulations of steady-state, mechanically forced homogeneous ma…

physics.flu-dyn2017★ 53 cited

Chaotic properties of a turbulent isotropic fluid

A. Berera, R. D. J. G. Ho

By tracking the divergence of two initially close trajectories in phase space in an Eulerian approach to forced turbulence, the relation between the maximal Lyapunov exponent ,…