Cooperative charged particle swarm optimiser. - Anna S. Rakitianskaia; Andries P. Engelbrecht (IEEE Congress on Evolutionary Computation, 2008)

The SeqWord Genome Browser: an online tool for the identification and visualization of atypical regions of bacterial genomes through oligonucleotide usage. - Hamilton Ganesan; Anna S. Rakitianskaia; Colin F. Davenport; Burkhard Tümmler; Oleg N. Reva (BMC Bioinform., 2008)

Training neural networks with PSO in dynamic environments. - Anna S. Rakitianskaia; Andries P. Engelbrecht (IEEE Congress on Evolutionary Computation, 2009)

Training feedforward neural networks with dynamic particle swarm optimisation. - Anna S. Rakitianskaia; Andries P. Engelbrecht (Swarm Intell., 2012)

Synchronizing to Learn and Like. - Roy Vink; Anna S. Bosman; Toon Cillessen (CogSci, 2013)

Training high-dimensional neural networks with cooperative particle swarm optimiser. - Anna S. Rakitianskaia; Andries P. Engelbrecht (IJCNN, 2014)

Weight regularisation in particle swarm optimisation neural network training. - Anna S. Rakitianskaia; Andries P. Engelbrecht (SIS, 2014)

Saturation in PSO neural network training: Good or evil? - Anna S. Rakitianskaia; Andries P. Engelbrecht (CEC, 2015)

Measuring Saturation in Neural Networks. - Anna S. Rakitianskaia; Andries P. Engelbrecht (SSCI, 2015)

Analysis of error landscapes in multi-layered neural networks for classification. - Anna S. Rakitianskaia; Eduan Bekker; Katherine M. Malan; Andries P. Engelbrecht (CEC, 2016)

Search space boundaries in neural network error landscape analysis. - Anna Sergeevna Bosman; Andries P. Engelbrecht; Mardé Helbig (SSCI, 2016)

Characterising neutrality in neural network error landscapes. - Willem Abraham van Aardt; Anna Sergeevna Bosman; Katherine Mary Malan (CEC, 2017)

Progressive gradient walk for neural network fitness landscape analysis. - Anna Sergeevna Bosman; Andries P. Engelbrecht; Mardé Helbig (GECCO (Companion), 2018)

Fitness Landscape Analysis of Weight-Elimination Neural Networks. - Anna S. Bosman; Andries P. Engelbrecht; Mardé Helbig (Neural Process. Lett., 2018)

Unsupervised Change Detection in Satellite Images Using Convolutional Neural Networks. - Kevin Louis de Jong; Anna Sergeevna Bosman (IJCNN, 2019)

Evolutionary Neural Architecture Search for Image Restoration. - Gerard Jacques van Wyk; Anna Sergeevna Bosman (IJCNN, 2019)

Loss Surface Modality of Feed-Forward Neural Network Architectures. - Anna Sergeevna Bosman; Andries P. Engelbrecht; Mardé Helbig (IJCNN, 2020)

Black-Box Saliency Map Generation Using Bayesian Optimisation. - Mamuku Mokuwe; Michael Burke; Anna Sergeevna Bosman (IJCNN, 2020)

Visualising basins of attraction for the cross-entropy and the squared error neural network loss functions. - Anna Sergeevna Bosman; Andries P. Engelbrecht; Mardé Helbig (Neurocomputing, 2020)

Analysing the loss landscape features of generative adversarial networks. - Jarrod Moses; Katherine M. Malan; Anna S. Bosman (GECCO Companion, 2021)

Characterisation of environment type and difficulty for streamed data classification problems. - Mathys Ellis; Anna S. Bosman; Andries P. Engelbrecht (Inf. Sci., 2021)

Genetic Micro-Programs for Automated Software Testing with Large Path Coverage. - Jarrod Goschen; Anna S. Bosman; Stefan Gruner (CEC, 2022)

A Local Optima Network Analysis of the Feedforward Neural Architecture Space. - Isak Potgieter; Christopher W. Cleghorn; Anna S. Bosman (IJCNN, 2022)

Cauchy Loss Function: Robustness Under Gaussian and Cauchy Noise. - Thamsanqa Mlotshwa; Heinrich van Deventer; Anna Sergeevna Bosman (SACAIR, 2022)

Hybridised Loss Functions for Improved Neural Network Generalisation. - Matthew C. Dickson; Anna S. Bosman; Katherine M. Malan (CoRR, 2022)

KASAM: Spline Additive Models for Function Approximation. - Heinrich van Deventer; Pieter Janse van Rensburg; Anna S. Bosman (CoRR, 2022)

ATLAS: Universal Function Approximator for Memory Retention. - Heinrich van Deventer; Anna S. Bosman (CoRR, 2022)

Comparision Of Adversarial And Non-Adversarial LSTM Music Generative Models. - Moseli Mots'oehli; Anna Sergeevna Bosman; Johan Pieter de Villiers (CoRR, 2022)

Quantifying and Visualizing the Sharpness of Attraction Basins in Neural Network Error Landscapes. - Isobel Bosman; Anna Sergeevna Bosman; Katherine Mary Malan (GECCO Companion, 2023)

Empirical Loss Landscape Analysis of Neural Network Activation Functions. - Anna Sergeevna Bosman; Andries P. Engelbrecht; Mardé Helbig (GECCO Companion, 2023)

Hilbert Curves for Efficient Exploratory Landscape Analysis Neighbourhood Sampling. - Johannes J. Pienaar; Anna S. Bosman; Katherine M. Malan (EvoApplications@EvoStar, 2024)

Distal Interference: Exploring the Limits of Model-Based Continual Learning. - Heinrich van Deventer; Anna Sergeevna Bosman (CoRR, 2024)

Regularised feed forward neural networks for streamed data classification problems. - Mathys Ellis; Anna S. Bosman; Andries P. Engelbrecht (Eng. Appl. Artif. Intell., 2024)

Denoising diffusion post-processing for low-light image enhancement. - Savvas Panagiotou; Anna S. Bosman (Pattern Recognit., 2024)

Multi-objective Evolutionary Neural Architecture Search for Recurrent Neural Networks. - Reinhard Booysen; Anna Sergeevna Bosman (Neural Process. Lett., 2024)

Balancing Complexity and Performance of Machine Learning Models for Avian Pests Sound Detection in Agricultural Environments. - Micheline Kazeneza; Anna Sergeevna Bosman; Destiny Kwabla Amenyedzi; Damien Hanyurwimfura; Emmanuel Ndashimye; Anthony Vodacek (IEEE Access, 2025)

Early detection of Phytophthora root rot in Eucalyptus using hyperspectral reflectance and machine learning. - Hendrik J. Esterhuizen; Bernard Slippers; Anna S. Bosman; Jolanda Roux; Wayne Jones; Tanay Bose; Almuth Hammerbacher (Comput. Electron. Agric., 2025)

Training feedforward neural networks with Bayesian hyper-heuristics. - Arné Schreuder; Anna S. Bosman; Andries P. Engelbrecht; Christopher W. Cleghorn (Inf. Sci., 2025)

Online Meta-learning for AutoML in Real-time (OnMAR). - Mia Gerber; Anna Sergeevna Bosman; Johan Pieter de Villiers (CoRR, 2025)