Conditional Probability Models for Deep Image Compression [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Deep Neural Networks trained as image auto-encoders have recently emerged as a promising direction for advancing the state-of-the-art in image compression.
Fabian Mentzer +4 more
semanticscholar +1 more source
New bivariate and multivariate log-normal distributions as models for insurance data
Results in Applied Mathematics, 2022 The body of most multivariate financial data sets can be well modeled by log-normal distributions. Yet not many multivariate log-normal distributions are available in the literature.
Saralees Nadarajah, Jiahang Lyu
doaj +1 more source
Multimodal Deep Generative Models for Trajectory Prediction: A Conditional Variational Autoencoder Approach [PDF]
IEEE Robotics and Automation Letters, 2020 Human behavior prediction models enable robots to anticipate how humans may react to their actions, and hence are instrumental to devising safe and proactive robot planning algorithms.
B. Ivanovic +3 more
semanticscholar +1 more source
Learning for Video Compression With Recurrent Auto-Encoder and Recurrent Probability Model [PDF]
IEEE Journal on Selected Topics in Signal Processing, 2020 The past few years have witnessed increasing interests in applying deep learning to video compression. However, the existing approaches compress a video frame with only a few number of reference frames, which limits their ability to fully exploit the ...
Ren Yang +3 more
semanticscholar +1 more source
New Checkable Conditions for Moment Determinacy of Probability Distributions [PDF]
Theory of Probability & Its Applications, 2020 Проанализированы некоторые условия, которые играют существенную роль при выяснении, однозначно ли данное вероятностное распределение определяется своими моментами. Мы предлагаем новые условия как для абсолютно непрерывных, так и для дискретных распределений.
Stoyanov, J. M., Lin, G. D., Kopanov, P.
openaire +2 more sources
Correlated Binomial Models and Correlation Structures [PDF]
, 2006 We discuss a general method to construct correlated binomial distributions by imposing several consistent relations on the joint probability function.
Bakkaloglu M +9 more
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Specification of the Conditional Expectation by Simple Linear Regression Model For Binomial Distribution Conditioned with Varying Sample Size. [PDF]
المجلة العراقية للعلوم الاحصائية, 2009 In this research, we consider the study of conditional expectation and it's relationship with regression model. The conditional expectation has a linear form which is specified as a simple linear regression model. The power transformation was used on the
doaj +1 more source
Conditional probability of distributed surface rupturing during normal-faulting earthquakes [PDF]
Solid Earth, 2021 Abstract. Coseismic surface faulting is a significant source of hazard for critical plants and distributive infrastructure; it may occur either on the principal fault or as distributed rupture on nearby faults. Hazard assessment for distributed faulting is based on empirical relations which, in the case of normal faults, were derived almost 15 years ...
Maria Francesca Ferrario, Franz Livio
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Conditional Generative Neural System for Probabilistic Trajectory Prediction [PDF]
IEEE/RJS International Conference on Intelligent RObots and Systems, 2019 Effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are critical for intelligent systems such as autonomous vehicles and wheeled mobile robotics navigating in complex scenarios to achieve safe ...
Jiachen Li, Hengbo Ma, M. Tomizuka
semanticscholar +1 more source