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Reactive Message Passing for Scalable Bayesian Inference
We introduce reactive message passing (RMP) as a framework for executing schedule-free, scalable, and, potentially, more robust message …
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RxInfer: A Julia package for reactive real-time Bayesian inference
Bayesian inference realizes optimal information processing through a full commitment to reasoning by probability theory. The Bayesian …
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Probabilistic programming with stochastic variational message passing
Stochastic approximation methods for variational inference have recently gained popularity in the probabilistic programming community …
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ReactiveMP.jl: A Julia package for reactive variational Bayesian inference
Variational Bayesian (VB) inference has become an increasingly popular method for approximating exact Bayesian inference in model-based …
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Active Inference and Epistemic Value in Graphical Models
The Free Energy Principle (FEP) postulates that biological agents perceive and interact with their environment in order to minimize a …
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AIDA: An active inference-Based design agent for audio processing algorithms
In this paper we present Active Inference-Based Design Agent (AIDA), which is an active inference-based agent that iteratively designs …
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On Epistemics in Expected Free Energy for Linear Gaussian State Space Models
Active Inference (AIF) is a framework that can be used both to describe information processing in naturally intelligent systems, such …
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A Bayesian Modeling Approach to Situated Design of Personalized Soundscaping Algorithms
Effective noise reduction and speech enhancement algorithms have great potential to enhance lives of hearing aid users by restoring …
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Bayesian pure-tone audiometry through active learning under informed priors
Pure-tone audiometry—the process of estimating a person’s hearing threshold from “audible” and “inaudible” responses to tones of …
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Extended Variational Message Passing for Automated Approximate Bayesian Inference
Variational Message Passing (VMP) provides an automatable and efficient algorithmic framework for approximating Bayesian inference in …
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