Artificial neural networks are inspired by the early models ... unit and its function is illustrated in Figure 1a. It receives input from a number of other units or external sources, weighs ...

As machine learning continues to revolutionize various industries, traditional neural networks face limitations when dealing ...

and information can be stored in terms of the thresholds set and the weight assigned by each neuron to each of its inputs. Artificial Neural Networks (ANNs) are designed to mimic the behaviour of the ...

On 17 October 2024, Martina Lamberti publicly defended her Ph.D. thesis, "Know the Past to See the Future: Memory and ...

For some tasks, like navigating a car down a road, the sheer multitude of input data and its relationship ... it can make more sense to create a neural network and train the computer to do the ...

John Hopfield and Geoffrey Hinton, the 2024 Physics Nobel laureates, developed computer systems that can memorise and learn ...

A new research paper from Canada has proposed a framework that deliberately introduces JPEG compression into the training ...

A liquid neural network can implement synaptic weights using nonlinear probabilities instead of simple scalar values. The synaptic connections and response times can adapt based on sensory inputs ...

In fusion experiments, understanding the behavior of the plasma, especially the ion temperature and rotation velocity, is ...