Marco Cox | BIASlabhttp://biaslab.org/author/marco-cox/Marco CoxHugo Blox Builder (https://hugoblox.com)en-usFri, 13 Aug 2021 07:41:37 +0100http://biaslab.org/author/marco-cox/avatar_hu_2ff89be2541b9d7c.jpgMarco Coxhttp://biaslab.org/author/marco-cox/Bayesian pure-tone audiometry through active learning under informed priorshttp://biaslab.org/publication/bayesian-pure-tone-audiometry-through-active-learning-under-informed-priors/Fri, 13 Aug 2021 07:41:37 +0100http://biaslab.org/publication/bayesian-pure-tone-audiometry-through-active-learning-under-informed-priors/A Factor Graph Approach to Automated Design of Bayesian Signal Processing Algorithmshttp://biaslab.org/publication/factor-graph-bayesian-signal-processing/Tue, 01 Jan 2019 14:50:37 +0100http://biaslab.org/publication/factor-graph-bayesian-signal-processing/ForneyLab.jl: Fast and flexible automated inference through message passing in Juliahttp://biaslab.org/publication/forneylab-fast-and-flexible/Fri, 05 Oct 2018 08:07:00 +0200http://biaslab.org/publication/forneylab-fast-and-flexible/ForneyLab: A Toolbox for Biologically Plausible Free Energy Minimization in Dynamic Neural Modelshttp://biaslab.org/publication/forneylab-biologically-plausible-fem/Sun, 23 Sep 2018 13:42:00 +0200http://biaslab.org/publication/forneylab-biologically-plausible-fem/Robust Expectation Propagation in Factor Graphs Involving Both Continuous and Binary Variableshttp://biaslab.org/publication/robust-expectation-propagation/Thu, 06 Sep 2018 14:07:00 +0200http://biaslab.org/publication/robust-expectation-propagation/ForneyLab.jl: a Julia Toolbox for Factor Graph-based Probabilistic Programminghttp://biaslab.org/publication/forneylab-julia-toolbox/Wed, 08 Aug 2018 13:36:00 +0200http://biaslab.org/publication/forneylab-julia-toolbox/A Probabilistic Modeling Approach to One-Shot Gesture Recognitionhttp://biaslab.org/publication/probabilistic-modeling-approach-to-one-shot-gesture-recognition/Fri, 06 Jul 2018 16:37:31 +0200http://biaslab.org/publication/probabilistic-modeling-approach-to-one-shot-gesture-recognition/A parametric approach to Bayesian optimization with pairwise comparisonshttp://biaslab.org/publication/parametric-bayesopt-with-pairwise-comparisons/Sun, 03 Dec 2017 16:37:31 +0200http://biaslab.org/publication/parametric-bayesopt-with-pairwise-comparisons/Variational Stabilized Linear Forgetting in State-Space Modelshttp://biaslab.org/publication/variational-slf-in-ssm/Sat, 30 Sep 2017 13:10:00 +0200http://biaslab.org/publication/variational-slf-in-ssm/A Gaussian process mixture prior for hearing loss modelinghttp://biaslab.org/publication/gp-mixture-prior-for-hearing-loss/Fri, 09 Jun 2017 16:37:31 +0200http://biaslab.org/publication/gp-mixture-prior-for-hearing-loss/An In-situ Trainable Gesture Classifierhttp://biaslab.org/publication/an-in-situ-trainable-gesture-classifier/Fri, 09 Jun 2017 16:37:31 +0200http://biaslab.org/publication/an-in-situ-trainable-gesture-classifier/CoHearhttp://biaslab.org/project/cohear/Wed, 01 Feb 2017 00:00:00 +0000http://biaslab.org/project/cohear/<p><strong>Hearing loss is a very serious health condition that has been associated with early dementia and cognitive decline. Still, hearing aid market penetration is quite low, in particular for the large population that is afflicted with ‘mild-to-moderate’ hearing impairment. This is mainly due to two reasons: Stigma (association with old age) and hearing aids (HA) sound quality. The recent commercial introduction of fashionable ‘hearables’ will likely alleviate the stigma issue. Recent advances in machine learning and cloud computing open new avenues for attacking the sound quality issue for hearing aids. In this project, we intend to develop a (crowd-based) collaborative design approach to improving the sound quality issues for the mild-to-moderately hearing-impaired population.</strong></p> <p>We expect to build a working prototype for collaboratively designed hearing algorithms that can be applied to a new class of ‘smart hearing devices’ with high appeal to the mild-to-moderately hearing-impaired patient. As an additional benefit, we hope that our technology will ease the transition from hearables to professional hearing aid technology for the moderate-to-profound hearing-impaired population.</p>A Bayesian binary classification approach to pure tone audiometryhttp://biaslab.org/publication/bayesian-pta/Thu, 10 Sep 2015 16:37:31 +0200http://biaslab.org/publication/bayesian-pta/