AI can transfer strange qualities through seemingly unrelated training—from a love of owls to something more dangerous ...

The researchers strengthened their findings with some theoretical results showing that, on some level, such subliminal ...

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch.

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.

Artificial neural networks learn better when they spend time not learning at all Periods off-line during training mitigated 'catastrophic forgetting' in computing systems Date: November 18, 2022 ...

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful.

Seeking to explore the capabilities of neural networks for recognizing and predicting motion, a group of researchers led by Hehe Fan developed and tested a deep learning approach based on relative ...

To help them explain the shocking success of deep neural networks, researchers are turning to older but better-understood models of machine learning.