5 papers
Restoring Neural Network Plasticity for Faster Transfer Learning
Xander Coetzer, Arné Schreuder, Anna Sergeevna Bosman
Transfer learning with models pretrained on ImageNet has become a standard practice in computer vision. Transfer learning refers to fine-tuning pretrained weights of a neural netwo…
Regularisation in neural networks: a survey and empirical analysis of approaches
Christiaan P. Opperman, Anna S. Bosman, Katherine M. Malan
Despite huge successes on a wide range of tasks, neural networks are known to sometimes struggle to generalise to unseen data. Many approaches have been proposed over the years to…
Prospecting MeerKAT Continuum Data for Enigmatic Radio Sources with Unsupervised Vector-Quantised Variational Autoencoders
Fernando L. Ventura, Kshitij Thorat, Anna Bosman +2
We present a novel application of Vector quantised variational autoencoders (VQ-VAEs) as an unsupervised tool to probe deep 1.28 GHz radio continuum images taken from the MeerKAT G…
Online Meta-learning for AutoML in Real-time (OnMAR)
Mia Gerber, Anna Sergeevna Bosman, Johan Pieter de Villiers
Automated machine learning (AutoML) is a research area focusing on using optimisation techniques to design machine learning (ML) algorithms, alleviating the need for a human to per…
Hilbert curves for efficient exploratory landscape analysis neighbourhood sampling
Johannes J. Pienaar, Anna S. Bosman, Katherine M. Malan
Landscape analysis aims to characterise optimisation problems based on their objective (or fitness) function landscape properties. The problem search space is typically sampled, an…