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Deep Neural Networks (DNNs) have shown great success in many fields. Various network architectures have been developed for different applications. Regardless of the complexities of the networks, DNNs do not provide model uncertainty. Bayesian Neural Networks (BNNs), on the other hand, is able to make probabilistic inference. Among various types of BNNs, Dropout as a Bayesian Approximation converts...
Instantaneous phase is a commonly used attribute for structural and stratigraphic feature characterization. The conventional calculation method is to construct the complex-valued seismic trace, then get the ratio of the imaginary part to the real part and fnally compute the antitangent of the ratio as the instantaneous phase attribute. In this way, the phase result at one time sample point is the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.