26 citations · 86 across the 21 of their papers we have counts for
4 papers · 1 filter
Fast Information-theoretic Bayesian Optimisation
Binxin Ru, Mark McLeod, Diego Granziol +1
Information-theoretic Bayesian optimisation techniques have demonstrated state-of-the-art performance in tackling important global optimisation problems. However, current informati…
Entropic Determinants
Diego Granziol, Stephen Roberts
The ability of many powerful machine learning algorithms to deal with large data sets without compromise is often hampered by computationally expensive linear algebra tasks, of whi…
Entropic Trace Estimates for Log Determinants
Jack Fitzsimons, Diego Granziol, Kurt Cutajar +3
The scalable calculation of matrix determinants has been a bottleneck to the widespread application of many machine learning methods such as determinantal point processes, Gaussian…
An information and field theoretic approach to the grand canonical ensemble
Diego Granziol, Stephen Roberts
We present a novel derivation of the constraints required to obtain the underlying principles of statistical mechanics using a maximum entropy framework. We derive the mean value c…