Hyderabad: Artificial Intelligence (AI) is transforming the way sleep disorders are diagnosed, with researchers at the ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

A biologically grounded computational model built to mimic real neural circuits, not trained on animal data, learned a visual categorization task just as actual lab animals do, matching their accuracy ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

Researchers at National University of Singapore used multiple interpretable machine learning methods to predict traffic congestion in in Alameda ...

In this video, we will look at the details of the RNN Model. We will see the mathematical equations for the RNN model, and ...

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Neuroscientists have been trying to understand how the human brain supports numerous advanced capabilities for centuries. The ...

Abstract: The absence of low-frequency (LF) components in seismic records leads to nonuniqueness in inversion, making the building of a reasonable LF model crucial for achieving high-precision ...

In this video, we will look at the details of the RNN Model. We will see the mathematical equations for the RNN model, and ...

Abstract: Unlike traditional feedforward neural networks, recurrent neural networks (RNNs) possess a recurrent connection that allows them to retain past information. This internal memory enables RNNs ...

The study points up interpretability as a critical barrier to trust and adoption. Many AI-based cybersecurity tools function as black boxes, producing alerts or classifications without clear ...