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Found 9 papers, 7 papers with code
Context-Aware Generative Models for Prediction of Aircraft Ground Tracks
These models are, therefore, agnostic to the intentions of the pilots and ATCOs, which can have a significant effect on the observed trajectory, particularly in the lateral plane.
MBORE: Multi-objective Bayesian Optimisation by Density-Ratio Estimation
In this work we present MBORE: multi-objective Bayesian optimisation by density-ratio estimation, and compare it to BO across a range of synthetic and real-world benchmarks.
How Bayesian Should Bayesian Optimisation Be?
FBBO using EI with an ARD kernel leads to the best performance in the noise-free setting, with much less difference between combinations of BO components when the noise is increased.
Asynchronous ε-Greedy Bayesian Optimisation
Batch Bayesian optimisation (BO) is a successful technique for the optimisation of expensive black-box functions.
What do you Mean? The Role of the Mean Function in Bayesian Optimisation
We show that the rate of convergence can depend sensitively on the choice of mean function.
$ε$-shotgun: $ε$-greedy Batch Bayesian Optimisation
Bayesian optimisation is a popular, surrogate model-based approach for optimising expensive black-box functions.
Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation
The performance of acquisition functions for Bayesian optimisation to locate the global optimum of continuous functions is investigated in terms of the Pareto front between exploration and exploitation.
Part-based Tracking by Sampling
We propose a novel part-based method for tracking an arbitrary object in challenging video sequences.
Visual Object Tracking: The Initialisation Problem
This BB may contain a large number of background pixels in addition to the object and can lead to parts-based tracking algorithms initialising their object models in background regions of the BB.
