49 citations · 173 across the 21 of their papers we have counts for
11 papers · 1 filter
Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity
Wolfgang Fruehwirt, Adam D. Cobb, Martin Mairhofer +11
As societies around the world are ageing, the number of Alzheimer's disease (AD) patients is rapidly increasing. To date, no low-cost, non-invasive biomarkers have been established…
BCCNet: Bayesian classifier combination neural network
Olga Isupova, Yunpeng Li, Danil Kuzin +3
Machine learning research for developing countries can demonstrate clear sustainable impact by delivering actionable and timely information to in-country government organisations (…
Intersectionality: Multiple Group Fairness in Expectation Constraints
Jack Fitzsimons, Michael Osborne, Stephen Roberts
Group fairness is an important concern for machine learning researchers, developers, and regulators. However, the strictness to which models must be constrained to be considered fa…
Automated bird sound recognition in realistic settings
Timos Papadopoulos, Stephen J. Roberts, Katherine J. Willis
We evaluated the effectiveness of an automated bird sound identification system in a situation that emulates a realistic, typical application. We trained classification algorithms…
Sequential sampling of Gaussian process latent variable models
Martin Tegner, Benjamin Bloem-Reddy, Stephen Roberts
We consider the problem of inferring a latent function in a probabilistic model of data. When dependencies of the latent function are specified by a Gaussian process and the data l…
Optimization, fast and slow: optimally switching between local and Bayesian optimization
Mark McLeod, Michael A. Osborne, Stephen J. Roberts
We develop the first Bayesian Optimization algorithm, BLOSSOM, which selects between multiple alternative acquisition functions and traditional local optimization at each step. Thi…