Want to understand how neural networks actually learn? This video breaks down forward and backward propagation in a simple, ...

Over the past decade, intensive studies have shown that the brain's meningeal lymphatic system acts as the brain's "waste ...

Confused about cost functions in neural networks? In this video, we break down what cost functions are, why they matter, and ...

Li, S. and Tan, Q. (2025) Bankruptcy Prediction in the Polish Banking Industry Using Principal Component Analysis and BP ...

Constrained deep learning is an advanced approach to training deep neural networks by incorporating domain-specific constraints into the learning process.

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

Get Instant Summarized Text (Gist) A self-attention neural network model enables rapid and accurate prediction of radiation shielding designs for space reactors, achieving less than 3% deviation ...

Leveraging the power of deep neural networks (DNNs) in optimization, we present a novel learning-based approach, the Constraint Boundary Wandering Framework (CBWF), to address these challenges. Our ...

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Abstract: In recent years, neural network models have been widely used in many tasks, however, tampering operations from malicious attackers, e.g., backdoor attacks and parameter malicious tampering, ...