Results 41 to 50 of about 11,193 (260)
Variational Inference of Kalman Filter and Its Application in Wireless Sensor Networks
International Journal of Distributed Sensor Networks, 2013 An improved Kalman filter algorithm by using variational inference (VIKF) is proposed. With variational method, the joint posterior distribution of the states is approximately decomposed into several relatively independent posterior distributions.
Zijian Dong, Tiecheng Song
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, 2015 We develop a general variational inference method that preserves dependency among the latent variables. Our method uses copulas to augment the families of distributions used in mean-field and structured approximations. Copulas model the dependency that is not captured by the original variational distribution, and thus the augmented variational family ...
Dustin Tran +2 more
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Variational inference for visual tracking [PDF]
2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003 The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or non-Gaussian functions, leading to analytically intractable inference. Solutions then require numerical approximation techniques, of which the particle filter is a popular choice.
Jaco Vermaak +2 more
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VIP - Variational Inversion Package with example implementations of Bayesian tomographic imaging
SeismicaBayesian inference has become an important methodology to solve inverse problems and to quantify uncertainties in their solutions. Variational inference is a method that provides probabilistic, Bayesian solutions efficiently by using optimisation.
Xin Zhang, Andrew Curtis
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Towards Autoencoding Variational Inference for Aspect-Based Opinion Summary
Applied Artificial Intelligence, 2019 Aspect-based Opinion Summary (AOS), consisting of aspect discovery and sentiment classification steps, has recently been emerging as one of the most crucial data mining tasks in e-commerce systems.
Tai Hoang, Huy Le, Tho Quan
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Simulating Active Inference Processes by Message Passing
Frontiers in Robotics and AI, 2019 The free energy principle (FEP) offers a variational calculus-based description for how biological agents persevere through interactions with their environment.
Thijs W. van de Laar +2 more
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Langevin Diffusion Variational Inference
CoRR, 2022 Many methods that build powerful variational distributions based on unadjusted Langevin transitions exist. Most of these were developed using a wide range of different approaches and techniques. Unfortunately, the lack of a unified analysis and derivation makes developing new methods and reasoning about existing ones a challenging task. We address this
Tomas Geffner, Justin Domke
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Neuroblastoma's complex, heterogeneous biology poses significant diagnostic and therapeutic challenges, often requiring caregivers to absorb complex information and participate in time‐sensitive decisions. However, caregivers often feel unprepared to evaluate options.
Vickie Buenger +8 more
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Platform motion estimation in multi-band synthetic aperture sonar with coupled variational autoencoders [PDF]
JASA Express LettersCoherent processing in synthetic aperture sonar (SAS) requires platform motion estimation and compensation with sub-wavelength accuracy for high-resolution imaging.
Angeliki Xenaki +2 more
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Uncertainty Quantification When Learning Dynamical Models and Solvers With Variational Methods
Journal of Advances in Modeling Earth Systems, 2023 In geosciences, data assimilation (DA) addresses the reconstruction of a hidden dynamical process given some observation data. DA is at the core of operational systems such as weather forecasting, operational oceanography and climate studies.
N. Lafon, R. Fablet, P. Naveau
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