(a) An illustrative map for Crack-Net, including the initial features, looping solver for data generation, model training, and prediction performance. (b) The Crack-Net architecture, which utilizes ...

Deep learning modeling that incorporates physical knowledge is currently a hot topic, and a number of excellent techniques have emerged. The most well-known one is the physics-informed neural networks ...

The Center for Deep Learning’s (CDL) mission is to act as a resource for companies seeking to establish or improve access to artificial intelligence (AI) by providing technical capacity and expertise, ...

HPE highlights recent research that explores the performance of GPUs in scale-out and scale-up scenarios for deep learning training. As companies begin to move deep learning projects from the ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Have you ever found yourself deep in the weeds of training a language model, wishing for a simpler way to make sense of its learning process? If you’ve struggled with the complexity of configuring ...

Scientists have long believed that foam behaves like glass, with bubbles locked into place. New simulations reveal that ...

A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and adaptive locomotion in simulation.