Paper-Conference

ForneyLab.jl: a Julia Toolbox for Factor Graph-based Probabilistic Programming
Scientific modeling concerns a continual search for better models for given data sets. This process can be elegantly captured in a …
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A Probabilistic Modeling Approach to One-Shot Gesture Recognition
Gesture recognition enables a natural extension of the way we currently interact with devices. Commercially available gesture …
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K-shot learning of acoustic context
In order to personalize the behavior of hearing aid devices in different acoustic scenes, we need personalized acoustic scene …
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A parametric approach to Bayesian optimization with pairwise comparisons
Optimizing a (preference) function through a small number of pairwise comparisons is challenging since pairwise comparisons provide …
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Variational Stabilized Linear Forgetting in State-Space Models
State-space modeling of non-stationary natural signals is a notoriously difficult task. As a result of context switches, the memory …
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A probabilistic modeling approach to hearing loss compensation
Hearing loss is a serious and prevalent condition that is characterized by a frequency-dependent loss of sensitivity for acoustic …
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A Gaussian process mixture prior for hearing loss modeling
Machine learning approaches to hearing loss estimation can significantly reduce the number of required experiments, but require a good …
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An In-situ Trainable Gesture Classifier
Gesture recognition, i.e., the recognition of pre-defined gestures by arm or hand movements, enables a natural extension of the way we …
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Probabilistic Inference-based Reinforcement Learning
We introduce probabilistic inference-based reinforcement learning (PIReL), an approach to solve decision making problems by treating …
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A Probabilistic Approach To Hearing Loss Compensation
Modern hearing aids use Dynamic Range Compression (DRC) as the primary solution to combat Hearing Loss (HL). Unfortunately, common DRC …
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