73 citations · 495 across the 39 of their papers we have counts for
4 papers · 2 filters
Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems
Rachmad Vidya Wicaksana Putra, Pasindu Wickramasinghe, Muhammad Shafique
The rising demand for energy-efficient edge AI systems (e.g., mobile agents/robots) has increased the interest in neuromorphic computing, since it offers ultra-low power/energy AI…
Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents
Rachmad Vidya Wicaksana Putra, Avaneesh Devkota, Muhammad Shafique
Training resource-constrained autonomous agents on multiple tasks simultaneously is crucial for adapting to diverse real-world environments. Recent works employ reinforcement learn…
QSViT: A Methodology for Quantizing Spiking Vision Transformers
Rachmad Vidya Wicaksana Putra, Saad Iftikhar, Muhammad Shafique
Vision Transformer (ViT)-based models have shown state-of-the-art performance (e.g., accuracy) in vision-based AI tasks. However, realizing their capability in resource-constrained…
Replay4NCL: An Efficient Memory Replay-based Methodology for Neuromorphic Continual Learning in Embedded AI Systems
Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad +2
Neuromorphic Continual Learning (NCL) paradigm leverages Spiking Neural Networks (SNNs) to enable continual learning (CL) capabilities for AI systems to adapt to dynamically changi…