4 papers
Hebbian-Oscillatory Co-Learning
Hasi Hays
We introduce Hebbian-Oscillatory Co-Learning (HOC-L), a unified two-timescale dynamical framework for joint structural plasticity and phase synchronization in bio-inspired sparse n…
Selective Synchronization Attention
Hasi Hays
The Transformer architecture has become the foundation of modern deep learning, yet its core self-attention mechanism suffers from quadratic computational complexity and lacks grou…
Resonant Sparse Geometry Networks
Hasi Hays
We introduce Resonant Sparse Geometry Networks (RSGN), a brain-inspired architecture with self-organizing sparse hierarchical input-dependent connectivity. Unlike Transformer archi…
Attention mechanisms in neural networks
Hasi Hays
Attention mechanisms represent a fundamental paradigm shift in neural network architectures, enabling models to selectively focus on relevant portions of input sequences through le…