Daniel N. Wilke

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 23

Top Topics

Gradient Projection

Top Venues

Appl. Math. Comput.

Adv. Eng. Softw.

Publications

Daniel N. Wilke
Multifidelity Surrogate Models: A New Data Fusion Perspective. CoRR (2024)
Stephan Schmidt, Daniel N. Wilke, Konstantinos C. Gryllias
Generalised envelope spectrum-based signal-to-noise objectives: Formulation, optimisation and application for gear fault detection under time-varying speed conditions. CoRR (2024)
Ryan Balshaw, P. Stephan Heyns, Daniel N. Wilke, Stephan Schmidt
A spectral regularisation framework for latent variable models designed for single channel applications. CoRR (2023)
Younghwan Chae, Daniel N. Wilke, Dominic Kafka
Gradient-only surrogate to resolve learning rates for robust and consistent training of deep neural networks. Appl. Intell. 53 (11) (2023)
Jesse Stevens, Daniel N. Wilke, Itumeleng Setshedi
Latent Space Perspicacity and Interpretation Enhancement (LS-PIE) Framework. CoRR (2023)
Johannes C. Joubert, Daniel N. Wilke, Patrick Pizette
On the momentum diffusion over multiphase surfaces with meshless methods. CoRR (2023)
Johann Bouwer, Daniel N. Wilke, Schalk Kok
A Novel and Fully Automated Domain Transformation Scheme for Near Optimal Surrogate Construction. CoRR (2023)
Jacob B. Cloete, Tinus Stander, Daniel N. Wilke
Parametric Circuit Fault Diagnosis Through Oscillation-Based Testing in Analogue Circuits: Statistical and Deep Learning Approaches. IEEE Access 10 (2022)
Dominic Kafka, Daniel N. Wilke
Resolving learning rates adaptively by locating stochastic non-negative associated gradient projection points using line searches. J. Glob. Optim. 79 (1) (2021)
Daniel N. Wilke
Traction chain networks: Insights beyond force chain networks for non-spherical particle systems. CoRR (2021)
Younghwan Chae, Daniel N. Wilke, Dominic Kafka
GOALS: Gradient-Only Approximations for Line Searches Towards Robust and Consistent Training of Deep Neural Networks. CoRR (2021)
Bradley Dean Collins, P. Stephan Heyns, Schalk Kok, Daniel N. Wilke
Application of Anti-Diagonal Averaging in Response Reconstruction. Symmetry 13 (7) (2021)
Dominic Kafka, Daniel N. Wilke
An empirical study into finding optima in stochastic optimization of neural networks. Inf. Sci. 560 (2021)
Dominic Kafka, Daniel N. Wilke
Investigating the interaction between gradient-only line searches and different activation functions. CoRR (2020)
Dominic Kafka, Daniel N. Wilke
Resolving learning rates adaptively by locating Stochastic Non-Negative Associated Gradient Projection Points using line searches. CoRR (2020)
Dominic Kafka, Daniel N. Wilke
Visual interpretation of the robustness of Non-Negative Associative Gradient Projection Points over function minimizers in mini-batch sampled loss functions. CoRR (2019)
Younghwan Chae, Daniel N. Wilke
Empirical study towards understanding line search approximations for training neural networks. CoRR (2019)
Marthinus N. Ras, Daniel N. Wilke, Albert A. Groenwold, Schalk Kok
On the rotational variance of the differential evolution algorithm. Adv. Eng. Softw. 136 (2019)
Dominic Kafka, Daniel N. Wilke
Gradient-only line searches: An Alternative to Probabilistic Line Searches. CoRR (2019)
Adolph J. Vogel, Daniel N. Wilke
Spatially distributed statistical significance approach for real parameter tuning with restricted budgets. Appl. Soft Comput. 70 (2018)
Nicolin Govender, Daniel N. Wilke, Patrick Pizette, Nor-Edine Abriak
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. 319 (2018)
Nicolin Govender, Daniel N. Wilke, Schalk Kok
Blaze-DEMGPU: Modular high performance DEM framework for the GPU architecture. SoftwareX 5 (2016)
Nicolin Govender, Daniel N. Wilke, Schalk Kok
Collision detection of convex polyhedra on the NVIDIA GPU architecture for the discrete element method. Appl. Math. Comput. 267 (2015)
Marthinus N. Ras, Daniel N. Wilke, Albert A. Groenwold, Schalk Kok
On rotationally invariant continuous-parameter genetic algorithms. Adv. Eng. Softw. 78 (2014)
Nicolin Govender, Daniel N. Wilke, Schalk Kok, Rosanne Els
Development of a convex polyhedral discrete element simulation framework for NVIDIA Kepler based GPUs. J. Comput. Appl. Math. 270 (2014)
Daniel N. Wilke, Schalk Kok, Albert A. Groenwold
Reference frame and scale invariant real-parameter genetic and differential evolution algorithms. GECCO (2007)
Schalk Kok, Daniel N. Wilke, Albert A. Groenwold
Recent Developments of the Particle Swarm Optimization Algorithm. Computational Intelligence (2005)