Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

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 ...

For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...

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, ...

Microsoft announced on-device training of machine language models with the open source ONNX Runtime (ORT). The ORT is a cross-platform machine-learning model accelerator, providing an interface to ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

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 ...