Modern neuroscience and the computational modeling of the activities of vast, integrated neural networks provide fruitful accounts of how our minds work and learn.

Encoding individual behavioral traits into a low-dimensional latent representation enables the accurate prediction of ...

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

A context-driven memory model simulates a wide range of characteristics of waking and sleeping hippocampal replay, providing a new account of how and why replay occurs.

Abstract: This article proposes a neural network (NN)-based calibration framework via quantization code reconstruction to address the critical limitation of multidimensional NNs (MDNNs) in ...

The demo runs entirely in your browser (no backend required) and shows an animated XOR training visualization.

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

Summary: A new study reveals that the brain’s basal ganglia use two distinct neural “languages” to control movement — one for learned skills and another for innate behaviors. Studying rats, ...

This is the PyTorch implementation of Legend-KINN, proposed by our paper "Legend-KINN: A Legendre Polynomial-Based Kolmogorov-Arnold-Informed Neural Network for Efficient PDE Solving", published in ...

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...