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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 ...

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 ...

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 ...

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 ...

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) ...

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 ...

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 ...

Stop Wasting your Cache! Bringing Machine Learning into Cache Computing

Chattez avec Graph Search

Deep learning-based galaxy image deconvolution

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

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

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

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

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

Explainability and Graph Learning From Social Interactions