21 citations · 30 across the 12 of their papers we have counts for
4 papers · 1 filter
Lock-in EP: An In-Situ Training Algorithm for Oscillatory Hardware
Sowjanya Tammali, Wilkie Olin-Ammentorp
Analog hardware platforms offer the potential to reduce energy consumption over digital architectures, but in order to succeed, large-scale analog systems must also be able to oper…
Residual and Attentional Architectures for Vector-Symbols
Wilkie Olin-Ammentorp Maxim Bazhenov
Vector-symbolic architectures (VSAs) provide methods for computing which are highly flexible and carry unique advantages. Concepts in VSAs are represented by 'symbols,' long vector…
Bridge Networks: Relating Inputs through Vector-Symbolic Manipulations
Wilkie Olin-Ammentorp, Maxim Bazhenov
Despite rapid progress, current deep learning methods face a number of critical challenges. These include high energy consumption, catastrophic forgetting, dependance on global los…
A Dual-Memory Architecture for Reinforcement Learning on Neuromorphic Platforms
Wilkie Olin-Ammentorp, Yury Sokolov, Maxim Bazhenov
Reinforcement learning (RL) is a foundation of learning in biological systems and provides a framework to address numerous challenges with real-world artificial intelligence applic…