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

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

Abstract: A new class of neural networks has been recently introduced to solve problems based on some physical model. Such networks are called “Physical-Informed Neural Networks” (PINN). PINN are ...

With the self-purification ability of lake-reservoir water body gradually weakened and the oscillation of dissolved oxygen (DO) concentration intensifying, the high-precision prediction of ...

If I ever encounter device issues in Windows, say to my keyboard, printer, Bluetooth, USB, or audio playback I use the Microsoft Support Diagnostic Tool (MSDT) which can run diagnostic packs to ...

Master the derivation of backpropagation with a clear, step-by-step explanation! Understand how neural networks compute gradients, update weights, and learn efficiently in this detailed tutorial.

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

Measurements at the Large Hadron Collider have been stymied by one of the most central phenomena of the quantum world. But now, a young researcher has championed a new method to solve the problem ...

Traipse into the world of artificial intelligence research, and it won’t take long to stumble across a concept known as the “singularity.” A loan word from astrophysics describing the heart of a black ...