Month: November 2022

Navigating Binaural Sound with Robust Contrastive Embeddings

Imagine you’re exploring a vast forest, trying to locate the source of different bird calls. It’s not an easy task, as the sound can bounce off trees and echo through the undergrowth. Similarly, when it comes to locating sound sources using binaural cues, traditional methods struggle with varying acoustic conditions. However, a recent study introduces […]

Published on November 16, 2022

Sparse measures with swarm-based pliable hidden Markov model and deep learning for EEG classification

Imagine you’re trying to solve a complex puzzle with pieces that constantly change shape. That’s how researchers feel when dealing with electroencephalography (EEG) signals, which are notoriously complex. But fear not! A group of clever scientists has come up with a new approach to tackle this challenge. They developed a versatile model to analyze and […]

Published on November 16, 2022

Bayesian continual learning via spiking neural networks

Just like biological brains, neuromorphic systems powered by spiking neural networks (SNNs) possess the remarkable abilities of energy efficiency, continual adaptation, and risk management. This study focuses on designing neuromorphic systems that can adapt to changing learning tasks while accurately estimating uncertainty. By applying a Bayesian continual learning framework, we develop online learning rules for […]

Published on November 16, 2022