INTERNAL wavesDEEP learningMACHINE learningPHYSICAL lawsMESOSCALE eddiesOCEANHigher-accuracy long-term ocean temperature prediction plays a critical role in ocean-related research fields and climate forecasting (e.g., oceanic internal waves and mesoscale eddies). The essential component of ...
Absence of this is called Internal Covariate shift, and this may slow down training. In this article, we will cover problems No. 1 and 2, and how activation functions are used to address them. We end with some practical advice to choose which activation function to chose for your deep ...
With the help of deep learning, neural networks can help transform the power of computers, helping them come even closer to human-like decision making.
In fact, information on the internal dynamic mechanisms and external driving forces of the ocean are already embedded in the time series of observations. Therefore, we can determine the patterns of ocean variations through data mining of these series to achieve forecasting. Furthermore, to predict ...
The Hamiltonian of a stably stratified incompressible fluid in an internal water wave in a deep ocean is constructed. Studying the ocean internal wave field with its full dynamics is formidable (or unsolvable) so we consider a test-wave Hamiltonian to study the dynamical and statistical properties...
The LSTM layer and an LSTM cell are shown schematically in Figs.1d and6a, respectively. The equations for the LSTM are shown as Eqs. (9)–(14)32,41. At a timet, the inputxtand two internal statesCt−1andht−1are fed into the LSTM cell. The first thing to be decided by the...
Underlined "TTS*" and "Judy*" areinternal🐸TTS models that are not released open-source. They are here to show the potential. Models prefixed with a dot (.Jofish .Abe and .Janice) are real human voices. Features High-performance Deep Learning models for Text2Speech tasks. ...
engineering and considerable domain expertise to design a feature extractor that transformed the raw data (such as the pixel values of an image) into a suitable internal representation or feature vector from which the learning subsystem, often a classifier, could detect or classify patterns in the ...
Deep learning-driven adaptive optics characterization First, we characterized the response accuracy of DL-AO network using controlled wavefront distortions generated by the deformable mirror. These wavefront distortions resulted in aberrated emission patterns, which were then collected and sent to DL-AO ...
Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer. To remain mathematically or computationally tractable, these models must rely on simplifying assumptions, thereby limiting t