Results 31 to 40 of about 199,039 (272)
Accelerating Bayesian microseismic event location with deep learning [PDF]
Solid Earth, 2021 We present a series of new open-source deep-learning algorithms to accelerate Bayesian full-waveform point source inversion of microseismic events. Inferring the joint posterior probability distribution of moment tensor components and source location is ...
A. Spurio Mancini +5 more
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Deep Learning: A Bayesian Perspective
Bayesian Analysis, 2017 Deep learning is a form of machine learning for nonlinear high dimensional pattern matching and prediction. By taking a Bayesian probabilistic perspective, we provide a number of insights into more efficient algorithms for optimisation and hyper-parameter tuning.
Polson, Nicholas G., Sokolov, Vadim
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, 2020 Department of Computer Science and EngineeringAs deep learning has grown fast, so did the desire to interpret deep learning black boxes. As a result, many analysis tools have emerged to interpret it.
Lee, Ginkyeng
core
Journal of Modern Power Systems and Clean Energy, 2022 Modern power systems are incorporated with distributed energy sources to be environmental-friendly and cost-effective. However, due to the uncertainties of the system integrated with renewable energy sources, effective strategies need to be adopted to ...
Shiyao Zhang, James J.Q. Yu
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High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models
, 2015 Learning in deep models using Bayesian methods has generated significant attention recently. This is largely because of the feasibility of modern Bayesian methods to yield scalable learning and inference, while maintaining a measure of uncertainty in the
Carin, Lawrence +3 more
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A Novel Method of Emergency Situation Evaluation for Deep-Sea Based on Bayesian Network
IEEE Access, 2020 In order to make effective emergency decisions timely, this paper proposes an intelligent emergency situation evaluation method based on the Bayesian network for deep-sea emergency response, which is used to evaluate the deep-sea emergency situation ...
Kun Lang, Dongsen Si, Zhihong Ma
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Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa
, 2018 This paper presents a generic Bayesian framework that enables any deep learning model to actively learn from targeted crowds. Our framework inherits from recent advances in Bayesian deep learning, and extends existing work by considering the targeted ...
Damianou, Andreas +3 more
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IEEE Access, 2021 Deep learning has demonstrated high accuracy for 3D object shape error modeling necessary to estimate dimensional and geometric quality defects in multi-station assembly systems (MAS).
Sumit Sinha +2 more
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Early Detection of the Advanced Persistent Threat Attack Using Performance Analysis of Deep Learning
IEEE Access, 2020 One of the most common and critical destructive attacks on the victim system is the advanced persistent threat (APT)-attack. An APT attacker can achieve its hostile goal through obtaining information and gaining financial benefits from the infrastructure
Javad Hassannataj Joloudari +5 more
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Bayesian Deep Learning for Dark Energy
, 2020 In this work we discuss basic ideas on how to structure and study the Bayesian methods for standard models of dark energy and how to implement them in the architecture of deep learning processes.
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