Search Results - Variational expected maximum algorithm

VGAEDTI: drug-target interaction prediction based on variational inference and graph autoencoder by Zhang, Yuanyuan, Feng, Yinfei, Wu, Mengjie, Deng, Zengqian, Wang, Shudong

“… One is variational graph autoencoder (VGAE) which is used…”
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Adaptive parameter estimation of GMM and its application in clustering by Zhao, Linchang, Shang, Zhaowei, Tan, Jin, Luo, Xiaoliu, Zhang, Taiping, Wei, Yu, Tang, Yuan Yan

“…) algorithm on the basis of the variational bayesian expected maximum (VBEM) to simultaneously implement the parameter estimation and select the optimal components of GMM…”
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Variational Bayes for continuous hidden Markov models and its application to active learning by Shihao Ji, Krishnapuram, B., Carin, L.

“…In this paper, we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs…”
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A stochastic Bregman golden ratio algorithm for non-Lipschitz stochastic mixed variational inequalities with application to resource share problems by Long, Xian-Jun, Yang, Jing

“… Since our algorithm only requires to calculate one stochastic approximation of the expected mapping per iteration, the computations can be reduced…”
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Twisted hybrid algorithms for combinatorial optimization by Caha, Libor, Kliesch, Alexander, Koenig, Robert

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SINS/EM Log Integrated Navigation With Variable-Structure Multiple Model Adaptive Kalman Filter by Ben, Yueyang, Wang, Jiancheng, Zang, Xinle, Li, Qian

“… To mitigate the adverse effects caused by the EM Log, an expected-mode augmentation variable-structure multiple model adaptive Kalman filter (EMA-VSMM-AKF…”
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A latent variable model for two-dimensional canonical correlation analysis and the variational inference by Safayani, Mehran, Momenzadeh, Saeid, Mirzaei, Abdolreza, Razavi, Masoomeh Sadat

“…The probabilistic dimension reduction has been and is a major concern. Probabilistic models provide a better interpretability of the dimension reduction…”
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Signal Recovery by Stochastic Optimization by Juditsky, A. B., Nemirovski, A. S.

“…We discuss an approach to signal recovery in Generalized Linear Models (GLM) in which the signal estimation problem is reduced to the problem of solving a stochastic monotone Variational Inequality (VI…”
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Note on an inertial projection-based approach for solving extended general quasi-variational inequalities and its convergence analysis by Jabeen, Saudia, Macías, Siegfried, Ullah, Saleem, Noor, Muhammad Aslam, Macías-Díaz, Jorge E.

“…In this work, an inertial projection-based method is proposed to find approximate solutions to a new class of quasi-variational inequalities…”
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Target Tracking Algorithm Based on Variational Bayes by Li, Yin, Lu, Yongchao, Mu, Yang

“…To address the problem of low tracking accuracy caused by unknown excitation and measurement noise in radar systems, a tracking algorithm based on variational Bayes is proposed…”
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Cone-beam X-ray luminescence computed tomography via Laplacian scale mixture prior-driven variational Bayesian method by He, Yiting, Yang, Bianbian, Cai, Nannan, Chen, Yi, Wang, Yifan, Yi, Huangjian, Hao, Xingxing, Gao, Chengyi, Cao, Xin

“… Here, a variational Bayesian method based on the Laplacian scale mixture prior has been proposed for the modeling and recovery of sparse signals for CB-XLCT…”
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A Variational Framework for Region-Based Segmentation Incorporating Physical Noise Models by Sawatzky, Alex, Tenbrinck, Daniel, Jiang, Xiaoyi, Burger, Martin

“… In the recent years mathematical models based on partial differential equations and variational methods have led to superior results in many applications, e.g., medical imaging…”
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R-FAC: Resilient Value Function Factorization for Multirobot Efficient Search With Individual Failure Probabilities by Guo, Hongliang, Kang, Qi, Yau, Wei-Yun, Chew, Chee-Meng, Rus, Daniela

“…This article investigates the resilient multirobot efficient search problem (R-MuRES), which aims at coordinating multiple robots to detect a "nonadversarial" moving target with the minimal expected time…”
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Variational Bayesian Reinforcement Learning with Regret Bounds by O'Donoghue, Brendan

“…In reinforcement learning the Q-values summarize the expected future rewards that the agent will attain…”
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Carbon flux bias estimation employing Maximum Likelihood Ensemble Filter (MLEF) by Zupanski, Dusanka, Denning, A. Scott, Uliasz, Marek, Zupanski, Milija, Schuh, Andrew E., Rayner, Peter J., Peters, Wouter, Corbin, Katherine D.

“…We evaluate the capability of an ensemble based data assimilation approach, referred to as Maximum Likelihood Ensemble Filter (MLEF…”
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Robustness to spontaneous emission of a variational quantum algorithm by Henriet, Loïc

“…We study theoretically the effects of dissipation on the performances of a variational quantum algorithm used to approximately solve a combinatorial optimization problem, the Maximum Independent Set…”
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An Efficient Gradient Projection Method for Stochastic Optimal Control Problem with Expected Integral State Constraint by Wang, Qiming, Liu, Wenbin

“…In this work, we present an efficient gradient projection method for solving a class of stochastic optimal control problem with expected integral state constraint…”
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Max-Cut Linear Binary Classifier Based on Quantum Approximate Optimization Algorithm by Wang, Jiaji, Wang, Yuqi, Li, Xi, Liu, Shiming, Zhuang, Junda, Qin, Chao

“… However, for the implementation of many existing quantum classification algorithms, a large number of qubits and quantum circuits with high complexity are still required…”
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On the failure of variational score matching for VAE models by Li Kevin Wenliang

“…Score matching (SM) is a convenient method for training flexible probabilistic models, which is often preferred over the traditional maximum-likelihood (ML) approach…”
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On Bayesian Posterior Mean Estimators in Imaging Sciences and Hamilton–Jacobi Partial Differential Equations by Darbon, Jérôme, Langlois, Gabriel P.

“…Variational and Bayesian methods are two widely used set of approaches to solve image denoising problems…”
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