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   Articles with "variational inference" as a keyword



Data‐Driven Information Perception for Complex Industrial Networks of Service Based on Hierarchical Interactive Graph Variational Inference

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recommendations! Published in 2025 at "International Journal of Robust and Nonlinear Control"

DOI: 10.1002/rnc.7908

Abstract: This article proposes a hierarchical interactive graph variational inference (HI‐GVI) approach to solve the data‐driven information perception problem in complex industrial networks of service. In the HI‐GVI approach, a multi‐layer latent graph structure is organized… read more here.

Keywords: variational inference; hierarchical interactive; graph variational; interactive graph ... See more keywords

Tree-based variational inference for Poisson log-normal models

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recommendations! Published in 2024 at "Statistics and Computing"

DOI: 10.1007/s11222-025-10668-w

Abstract: When studying ecosystems, hierarchical trees are often used to organize entities based on proximity criteria, such as the taxonomy in microbiology, social classes in geography, or product types in retail businesses, offering valuable insights into… read more here.

Keywords: log normal; poisson log; model; variational inference ... See more keywords

Variational inference of ice shelf rheology with physics-informed machine learning

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recommendations! Published in 2023 at "Journal of Glaciology"

DOI: 10.1017/jog.2023.8

Abstract: Floating ice shelves that fringe the coast of Antarctica resist the flow of grounded ice into the ocean. One of the key factors governing the amount of flow resistance an ice shelf provides is the… read more here.

Keywords: rigidity; ice; physics; rheology ... See more keywords

Variational inference as an alternative to MCMC for parameter estimation and model selection

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recommendations! Published in 2022 at "Publications of the Astronomical Society of Australia"

DOI: 10.1017/pasa.2021.64

Abstract: Abstract Most applications of Bayesian Inference for parameter estimation and model selection in astrophysics involve the use of Monte Carlo techniques such as Markov Chain Monte Carlo (MCMC) and nested sampling. However, these techniques are… read more here.

Keywords: model selection; estimation; variational inference; inference ... See more keywords

Doubly Adaptive Importance Sampling

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recommendations! Published in 2024 at "Journal of Computational and Graphical Statistics"

DOI: 10.1080/10618600.2025.2530048

Abstract: We propose an adaptive importance sampling scheme for Gaussian approximations of intractable posteriors. Optimization-based approximations like variational inference can be too inaccurate while existing Monte Carlo methods can be too slow. Therefore, we propose a… read more here.

Keywords: importance; adaptive importance; doubly adaptive; variational inference ... See more keywords

Stochastic Variational Inference for Bayesian Phylogenetics: A Case of CAT Model

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recommendations! Published in 2019 at "Molecular Biology and Evolution"

DOI: 10.1093/molbev/msz020

Abstract: Abstract The pattern of molecular evolution varies among gene sites and genes in a genome. By taking into account the complex heterogeneity of evolutionary processes among sites in a genome, Bayesian infinite mixture models of… read more here.

Keywords: inference; inference bayesian; stochastic variational; variational inference ... See more keywords

A Variational Inference-Based LSTM-Enhanced Deep Neural Model for Sequential Recommendations

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3570636

Abstract: Long Short-Term Memory (LSTM) networks are particularly useful in recommender systems since user preferences change over time. Unlike traditional recommender models which assume static user-item interactions, LSTM models capture sequential dependencies and temporal dynamics, making… read more here.

Keywords: recommender; inference based; variational inference; model ... See more keywords

Transformer-Based Online Bayesian Neural Networks for Grant-Free Uplink Access in CRAN With Streaming Variational Inference

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recommendations! Published in 2022 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2021.3113679

Abstract: We propose a model-driven Bayesian deep learning framework for multiple access uplink systems in Multiuser MIMO systems. Utilizing tools from Streaming Variational Inference, we combine graphical models with neural networks to enable fast online machine… read more here.

Keywords: neural networks; streaming variational; transformer based; access ... See more keywords

VariFi: Variational Inference for Indoor Pedestrian Localization and Tracking Using IMU and WiFi RSS

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recommendations! Published in 2023 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2022.3232740

Abstract: Accurate indoor pedestrian localization and tracking are crucial in many practical applications. One efficient yet low-cost sensing scheme is the integration of inertial measurement unit and WiFi received signal strength (RSS) due to the popularity… read more here.

Keywords: localization; indoor pedestrian; pedestrian localization; rss ... See more keywords
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Advanced NOMA Receivers From a Unified Variational Inference Perspective

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recommendations! Published in 2021 at "IEEE Journal on Selected Areas in Communications"

DOI: 10.1109/jsac.2020.3018834

Abstract: Non-orthogonal multiple access (NOMA) on shared resources has been identified as a promising technology in 5G to improve resource efficiency and support massive access in all kinds of transmission modes. Power domain and code domain… read more here.

Keywords: unified variational; noma receivers; inference perspective; perspective ... See more keywords

Design of Communication Systems Using Deep Learning: A Variational Inference Perspective

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recommendations! Published in 2020 at "IEEE Transactions on Cognitive Communications and Networking"

DOI: 10.1109/tccn.2020.2985371

Abstract: Recent research in the design of end to end communication system using deep learning has produced models which can outperform traditional communication schemes. Most of these architectures leveraged autoencoders to design the encoder at the… read more here.

Keywords: communication; variational inference; communication systems; using deep ... See more keywords