This valuable study links psychological theories of chunking with a physiological implementation based on short-term synaptic plasticity and synaptic augmentation. The theoretical derivation for ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

For more than a century, scientists have wondered why physical structures like blood vessels, neurons, tree branches, and ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...

Abstract: To perform reliable information processing in quantum computers, quantum error correction (QEC) codes are essential for the detection and correction of ...

Microsoft is building a team dedicated to eliminating “every line of C and C++ from Microsoft by 2030,” which might touch Windows 11. While C powers the bulk of the Windows kernel and low-level ...

Microsoft is taking an impressive step in modernizing its biggest codebases and will eliminate all C/C++ code by the end of the decade, replacing it with Rust. “My goal is to eliminate every line of C ...

Abstract: Ordered statistics decoding has been instrumental in addressing decoding failures that persist after normalized min-sum decoding in short low-density parity-check codes. Despite its benefits ...

We introduce the NiNo model predicting future (nowcasting) parameters by learning neuron interaction in vision and language tasks. We feed c (c=5 by default) past parameter states as input to NiNo and ...