Daniel N. Wilke

Orcid: 0000-0002-8718-330X

According to our database1, Daniel N. Wilke authored at least 27 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Generalised envelope spectrum-based signal-to-noise objectives: Formulation, optimisation and application for gear fault detection under time-varying speed conditions.
CoRR, 2024

Multifidelity Surrogate Models: A New Data Fusion Perspective.
CoRR, 2024

2023
Gradient-only surrogate to resolve learning rates for robust and consistent training of deep neural networks.
Appl. Intell., June, 2023

A spectral regularisation framework for latent variable models designed for single channel applications.
CoRR, 2023

Latent Space Perspicacity and Interpretation Enhancement (LS-PIE) Framework.
CoRR, 2023

A Novel and Fully Automated Domain Transformation Scheme for Near Optimal Surrogate Construction.
CoRR, 2023

On the momentum diffusion over multiphase surfaces with meshless methods.
CoRR, 2023

2022
Parametric Circuit Fault Diagnosis Through Oscillation-Based Testing in Analogue Circuits: Statistical and Deep Learning Approaches.
IEEE Access, 2022

2021
Application of Anti-Diagonal Averaging in Response Reconstruction.
Symmetry, 2021

Resolving learning rates adaptively by locating stochastic non-negative associated gradient projection points using line searches.
J. Glob. Optim., 2021

An empirical study into finding optima in stochastic optimization of neural networks.
Inf. Sci., 2021

Traction chain networks: Insights beyond force chain networks for non-spherical particle systems.
CoRR, 2021

GOALS: Gradient-Only Approximations for Line Searches Towards Robust and Consistent Training of Deep Neural Networks.
CoRR, 2021

2020
Gradient-only line searches to automatically determine learning rates for a variety of stochastic training algorithms.
CoRR, 2020

Investigating the interaction between gradient-only line searches and different activation functions.
CoRR, 2020

2019
Empirical study towards understanding line search approximations for training neural networks.
CoRR, 2019

Gradient-only line searches: An Alternative to Probabilistic Line Searches.
CoRR, 2019

Visual interpretation of the robustness of Non-Negative Associative Gradient Projection Points over function minimizers in mini-batch sampled loss functions.
CoRR, 2019

On the rotational variance of the differential evolution algorithm.
Adv. Eng. Softw., 2019

2018
Spatially distributed statistical significance approach for real parameter tuning with restricted budgets.
Appl. Soft Comput., 2018

A study of shape non-uniformity and poly-dispersity in hopper discharge of spherical and polyhedral particle systems using the Blaze-DEM GPU code.
Appl. Math. Comput., 2018

2016
Blaze-DEMGPU: Modular high performance DEM framework for the GPU architecture.
SoftwareX, 2016

2015
Collision detection of convex polyhedra on the NVIDIA GPU architecture for the discrete element method.
Appl. Math. Comput., 2015

2014
Development of a convex polyhedral discrete element simulation framework for NVIDIA Kepler based GPUs.
J. Comput. Appl. Math., 2014

On rotationally invariant continuous-parameter genetic algorithms.
Adv. Eng. Softw., 2014

2007
Reference frame and scale invariant real-parameter genetic and differential evolution algorithms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2007

2005
Recent Developments of the Particle Swarm Optimization Algorithm.
Proceedings of the IASTED International Conference on Computational Intelligence, 2005


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