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Stop Wasting your Cache! Bringing Machine Learning into Cache Computing

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Publications associées (27)

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Deep learning-based galaxy image deconvolution

Frédéric Courbin, Pascale Jablonka, Utsav Akhaury

With the onset of large-scale astronomical surveys capturing millions of images, there is an increasing need to develop fast and accurate deconvolution algorithms that generalize well to different images. A powerful and accessible deconvolution method woul ...

FRONTIERS MEDIA SA2022

Offshore wind farm wake modelling using deep feed forward neural networks for active yaw control and layout optimisation

Sokratis Anagnostopoulos

Offshore wind farm modelling has been an area of rapidly increasing interest over the last two decades, with numerous analytical as well as computational-based approaches developed, in an attempt to produce designs that improve wind farm efficiency in powe ...

IOP PUBLISHING LTD2022

PlaceNet: A multi-scale semantic-aware model for visual loop closure detection

Hussein Fadl Hassan Hassan Osman

Loop closure detection helps simultaneous localization and mapping systems reduce map and state uncertainty via recognizing previously visited places along the path of a mobile robot. However, visual loop closure detection is susceptible to scenes with dyn ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Discovery of Slow Variables in a Class Of Multiscale Stochastic Systems Via Neural Networks

Przemyslaw Zielinski, Jan Sickmann Hesthaven

Finding a reduction of complex, high-dimensional dynamics to its essential, low-dimensional "heart" remains a challenging yet necessary prerequisite for designing efficient numerical approaches. Machine learning methods have the potential to provide a gene ...

2022

3D reconstruction of curvilinear structures with stereo matching deep convolutional neural networks

Pascal Fua, Cécile Hébert, Emad Oveisi, Anastasiia Mishchuk, Okan Altingövde, Gulnaz Ganeeva

Curvilinear structures frequently appear in microscopy imaging as the object of interest. Crystallographic defects, i.e dislocations, are one of the curvilinear structures that have been repeatedly investigated under transmission electron microscopy (TEM) ...

ELSEVIER2022

Revealing Morphology Evolution of Lithium Dendrites by Large-Scale Simulation Based on Machine Learning Force Field

Mouyi Weng

Solving the dendrite growth problem is critical for the development of lithium metal anode for high-capacity batteries. In this work, a machine learning force field model in combination with a self-consistent continuum solvation model is used to simulate t ...

WILEY-V C H VERLAG GMBH2022

Explainability and Graph Learning From Social Interactions

Ali H. Sayed, Stefan Vlaski, Valentina Shumovskaia, Konstantinos Ntemos

Social learning algorithms provide models for the formation of opinions over social networks resulting from local reasoning and peer-to-peer exchanges. Interactions occur over an underlying graph topology, which describes the flow of information among the ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022