125 citations · 189 across the 16 of their papers we have counts for
17 papers
Accelerating Multi-Objective Bayesian Optimisation via Predictive-Gradient Catalysts
Alma Rahat, Tinkle Chugh, Jonathan Fieldsend +1
This paper presents a general acceleration mechanism for multi-objective Bayesian optimisation (MOBO) that leverages Gaussian process predictive gradients as auxiliary signals. Rat…
CAPRI-CT: Causal Analysis and Predictive Reasoning for Image Quality Optimization in Computed Tomography
Sneha George Gnanakalavathy, Hairil Abdul Razak, Robert Meertens +3
In computed tomography (CT), achieving high image quality while minimizing radiation exposure remains a key clinical challenge. This paper presents CAPRI-CT, a novel causal-aware d…
DIMBA: Discretely Masked Black-Box Attack in Single Object Tracking
Xiangyu Yin, Wenjie Ruan, Jonathan Fieldsend
The adversarial attack can force a CNN-based model to produce an incorrect output by craftily manipulating human-imperceptible input. Exploring such perturbations can help us gain…
PRoA: A Probabilistic Robustness Assessment against Functional Perturbations
Tianle Zhang, Wenjie Ruan, Jonathan E. Fieldsend
In safety-critical deep learning applications robustness measurement is a vital pre-deployment phase. However, existing robustness verification methods are not sufficiently practic…
Efficient Approximation of Expected Hypervolume Improvement using Gauss-Hermite Quadrature
Alma Rahat, Tinkle Chugh, Jonathan Fieldsend +2
Many methods for performing multi-objective optimisation of computationally expensive problems have been proposed recently. Typically, a probabilistic surrogate for each objective…
Variational Autoencoders Without the Variation
Gregory A. Daly, Jonathan E. Fieldsend, Gavin Tabor
Variational autoencdoers (VAE) are a popular approach to generative modelling. However, exploiting the capabilities of VAEs in practice can be difficult. Recent work on regularised…