67 citations · 233 across the 19 of their papers we have counts for
4 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…
Bayesian Deep Learning for Exoplanet Atmospheric Retrieval
Frank Soboczenski, Michael D. Himes, Molly D. O'Beirne +8
Over the past decade, the study of extrasolar planets has evolved rapidly from plain detection and identification to comprehensive categorization and characterization of exoplanet…
Loss-Calibrated Approximate Inference in Bayesian Neural Networks
Adam D. Cobb, Stephen J. Roberts, Yarin Gal
Current approaches in approximate inference for Bayesian neural networks minimise the Kullback-Leibler divergence to approximate the true posterior over the weights. However, this…
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus
Adam D. Cobb, Richard Everett, Andrew Markham +1
In systems of multiple agents, identifying the cause of observed agent dynamics is challenging. Often, these agents operate in diverse, non-stationary environments, where models re…