Daniel N. Wilke

31 papers A 1Journal 29Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Towards a data-scale independent regulariser for robust sparse identification of non-linear dynamics. CoRR Jay Raut, Daniel N. Wilke, Stephan Schmidt
2025	J	`jnl`	Design for Sensing and Digitalisation (DSD): A Modern Approach to Engineering Design. CoRR Daniel N. Wilke
2025	J	`jnl`	Spectrally regularised LVMs: A spectral regularisation framework for latent variable models designed for single-channel applications. SoftwareX Ryan Balshaw, P. Stephan Heyns, Daniel N. Wilke, Stephan Schmidt
2025	J	`jnl`	Towards scientific machine learning for granular material simulations - challenges and opportunities. CoRR Marc Fransen, Andreas Fürst, Deepak Tunuguntla, Daniel N. Wilke, Benedikt Alkin, Daniel Barreto, Johannes Brandstetter, Miguel Angel Cabrera, Xinyan Fan, Mengwu Guo, Bram Kieskamp, Krishna Kumar, John Morrissey, Jonathan Nuttall, Jin Y. Ooi, Luisa Orozco, Stefanos-Aldo Papanicolopulos, Tongming Qu, Dingena Schott, Takayuki Shuku, WaiChing Sun, Thomas Weinhart, Dongwei Ye, Hongyang Cheng
2024	J	`jnl`	Generalised envelope spectrum-based signal-to-noise objectives: Formulation, optimisation and application for gear fault detection under time-varying speed conditions. CoRR Stephan Schmidt, Daniel N. Wilke, Konstantinos C. Gryllias
2024	J	`jnl`	Multifidelity Surrogate Models: A New Data Fusion Perspective. CoRR Daniel N. Wilke
2023	J	`jnl`	A Novel and Fully Automated Domain Transformation Scheme for Near Optimal Surrogate Construction. CoRR Johann Bouwer, Daniel N. Wilke, Schalk Kok
2023	J	`jnl`	A spectral regularisation framework for latent variable models designed for single channel applications. CoRR Ryan Balshaw, P. Stephan Heyns, Daniel N. Wilke, Stephan Schmidt
2023	J	`jnl`	Gradient-only surrogate to resolve learning rates for robust and consistent training of deep neural networks. Appl. Intell. Younghwan Chae, Daniel N. Wilke, Dominic Kafka
2023	J	`jnl`	Latent Space Perspicacity and Interpretation Enhancement (LS-PIE) Framework. CoRR Jesse Stevens, Daniel N. Wilke, Itumeleng Setshedi
2023	J	`jnl`	On the momentum diffusion over multiphase surfaces with meshless methods. CoRR Johannes C. Joubert, Daniel N. Wilke, Patrick Pizette
2022	J	`jnl`	Parametric Circuit Fault Diagnosis Through Oscillation-Based Testing in Analogue Circuits: Statistical and Deep Learning Approaches. IEEE Access Jacob B. Cloete, Tinus Stander, Daniel N. Wilke
2021	J	`jnl`	An empirical study into finding optima in stochastic optimization of neural networks. Inf. Sci. Dominic Kafka, Daniel N. Wilke
2021	J	`jnl`	Application of Anti-Diagonal Averaging in Response Reconstruction. Symmetry Bradley Dean Collins, P. Stephan Heyns, Schalk Kok, Daniel N. Wilke
2021	J	`jnl`	GOALS: Gradient-Only Approximations for Line Searches Towards Robust and Consistent Training of Deep Neural Networks. CoRR Younghwan Chae, Daniel N. Wilke, Dominic Kafka
2021	J	`jnl`	Resolving learning rates adaptively by locating stochastic non-negative associated gradient projection points using line searches. J. Glob. Optim. Dominic Kafka, Daniel N. Wilke
2021	J	`jnl`	Traction chain networks: Insights beyond force chain networks for non-spherical particle systems. CoRR Daniel N. Wilke
2020	J	`jnl`	Investigating the interaction between gradient-only line searches and different activation functions. CoRR Dominic Kafka, Daniel N. Wilke
2020	J	`jnl`	Resolving learning rates adaptively by locating Stochastic Non-Negative Associated Gradient Projection Points using line searches. CoRR Dominic Kafka, Daniel N. Wilke
2019	J	`jnl`	Empirical study towards understanding line search approximations for training neural networks. CoRR Younghwan Chae, Daniel N. Wilke
2019	J	`jnl`	Gradient-only line searches: An Alternative to Probabilistic Line Searches. CoRR Dominic Kafka, Daniel N. Wilke
2019	J	`jnl`	On the rotational variance of the differential evolution algorithm. Adv. Eng. Softw. Marthinus N. Ras, Daniel N. Wilke, Albert A. Groenwold, Schalk Kok
2019	J	`jnl`	Visual interpretation of the robustness of Non-Negative Associative Gradient Projection Points over function minimizers in mini-batch sampled loss functions. CoRR Dominic Kafka, Daniel N. Wilke
2018	J	`jnl`	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. Nicolin Govender, Daniel N. Wilke, Patrick Pizette, Nor-Edine Abriak
2018	J	`jnl`	Spatially distributed statistical significance approach for real parameter tuning with restricted budgets. Appl. Soft Comput. Adolph J. Vogel, Daniel N. Wilke
2016	J	`jnl`	Blaze-DEMGPU: Modular high performance DEM framework for the GPU architecture. SoftwareX Nicolin Govender, Daniel N. Wilke, Schalk Kok
2015	J	`jnl`	Collision detection of convex polyhedra on the NVIDIA GPU architecture for the discrete element method. Appl. Math. Comput. Nicolin Govender, Daniel N. Wilke, Schalk Kok
2014	J	`jnl`	Development of a convex polyhedral discrete element simulation framework for NVIDIA Kepler based GPUs. J. Comput. Appl. Math. Nicolin Govender, Daniel N. Wilke, Schalk Kok, Rosanne Els
2014	J	`jnl`	On rotationally invariant continuous-parameter genetic algorithms. Adv. Eng. Softw. Marthinus N. Ras, Daniel N. Wilke, Albert A. Groenwold, Schalk Kok
2007	A	`conf`	Reference frame and scale invariant real-parameter genetic and differential evolution algorithms. GECCO Daniel N. Wilke, Schalk Kok, Albert A. Groenwold
2005	—	`conf`	Recent Developments of the Particle Swarm Optimization Algorithm. Computational Intelligence Schalk Kok, Daniel N. Wilke, Albert A. Groenwold