Results 61 to 70 of about 5,051,769 (292)
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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Stochastic variational inference for large-scale discrete choice models using adaptive batch sizes
, 2015 Discrete choice models describe the choices made by decision makers among alternatives and play an important role in transportation planning, marketing research and other applications. The mixed multinomial logit (MMNL) model is a popular discrete choice
Tan, Linda S. L.
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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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AdamB: Decoupled Bayes by Backprop With Gaussian Scale Mixture Prior
IEEE Access, 2022 Overfitting of neural networks to training data is one of the most significant problems in machine learning. Bayesian neural networks (BNNs) are known to be robust against overfitting owing to their ability to model parameter uncertainty.
Keigo Nishida, Makoto Taiji
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Automatic Variational Inference in Stan [PDF]
, 2015 Variational inference is a scalable technique for approximate Bayesian inference. Deriving variational inference algorithms requires tedious model-specific calculations; this makes it difficult to automate.
Blei, David M. +3 more
core
Pediatric Blood &Cancer, EarlyView.ABSTRACT End‐of‐life conversations with adolescents and young adults (AYAs) with cancer rarely occur without the guidance of healthcare professionals. As a part of the ‘Difficult Discussions’ study, focused on palliative care and advance care planning discussions with AYAs with cancer, we investigated the factors that healthcare professionals identify ...
Justine Lee +9 more
wiley +1 more source
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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A primer on Variational Laplace (VL)
NeuroImage, 2023 This article details a scheme for approximate Bayesian inference, which has underpinned thousands of neuroimaging studies since its introduction 15 years ago.
Peter Zeidman, Karl Friston, Thomas Parr
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