From writing and typing to playing a musical instrument or mastering a sport, learning movement-based tasks is one of the ...

Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure ... An artificial neural network can be created by simulating ...

Often, each node in a layer is connected to every node in the subsequent layer to send information forward in the network. “When you write code to build an artificial neural network, you're basically ...

The study provides compelling evidence that local dopamine release serves as a crucial signal for neural plasticity in the motor cortex, enabling the necessary adaptations for producing precise and ...

A new study proposes NdLinear, a multi-dimensional linear layer that preserves data structure and slashes parameter counts ...

Unlike traditional neural networks, which require extensive ... Inspired by how the brain works, RC uses a fixed network structure but learns the outputs in an adaptable way.

Researchers have mapped the long-range synaptic connections involved in vocal learning in zebra finches, uncovering new ...

Systolic arrays never took off when they first emerged, but they are shaping up as the dominant ways to structure an AI ... can keep the entirety of the neural network on die," he said.

Research team designed PBCounter, a weighted model counting solver for pseudo-Boolean formulas. It uses variable elimination and dynamic programming with ADDs, outperforming state-of-the-art CNF-based ...