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

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back ...

Beyond big projects, doing smaller, focused exercises is super helpful. GeeksforGeeks has tons of these, covering everything ...

The typical scaling law of neural networks suggests that accuracy is improved with larger models, which is to say, more neurons. Liquid neural networks may break this law to show that scale is not ...

Based on our results, we recommend Graph Neural Networks for physics simulation workloads. The TF-GNN API has a steep initial learning curve for using its data layer, especially if there is no data ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Researchers report abnormalities in functional neural networks of dogs diagnosed with anxiety. The study shows that compared with healthy dogs, those with anxiety exhibit stronger connections ...

OpenAI peeks into the “black box” of neural networks with new research "We do not understand" how LLMs work, admits OpenAI in quest to make them interpretable.