Using the time series signal of pipeline cracks as the original dataset, local features of the original dataset are extracted through one-dimensional convolutional neural network, and the global ...

The notebooks go into extreme details to ensure a proper, robust fundamental understanding of the deep learning concepts being covered ... then proceeds to multi-layer perceptrons (MLPs), ...

Based on the deep learning method, the convolutional neural network model is used to extract the newly produced 3D feature to achieve load identification in this paper. The results indicate the new 3D ...

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch ...

A new communication-collective system, OptiReduce, speeds up AI and machine learning training across multiple cloud servers by setting time boundaries rather than waiting for every server to catch up, ...

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial ...

Another research line that Rus is excited about to make robots smarter was inspired by the development of large language ...

Now, preparations have begun on its fifth as NASA works to increase the network's capacity. NASA's Deep Space Network facility in Canberra, Australia celebrated its 60th anniversary on March 19 ...

Perceived similarity offers a window into the mental representations underlying our ability to make sense of our visual world, yet, the collection of similarity judgments quickly becomes infeasible ...