Deep Learning with Yacine on MSN
Stochastic depth for neural networks – explained clearly
A simple and clear explanation of stochastic depth — a powerful regularization technique that improves deep neural network ...
This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...
Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...
Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...
The best way to understand neural networks is to build one for yourself. Let's get started with creating and training a neural network in Java. Artificial neural networks are a form of deep learning ...
The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...
New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers ...
Deep Learning with Yacine on MSN
Highway networks – deep neural network explained
Explore Highway Networks, a neural network architecture designed to improve training of deep networks. Concepts and examples explained. #HighwayNetworks #DeepLearning #NeuralNetworks ...
“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...
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