Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing

8 July 2024

Papers citing "Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing"

6 / 6 papers shown

Title
FLAMES: A Hybrid Spiking-State Space Model for Adaptive Memory Retention in Event-Based Learning Biswadeep Chakraborty Saibal Mukhopadhyay 40 0 0 02 Apr 2025
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks Biswadeep Chakraborty H. Kumar Saibal Mukhopadhyay 75 1 0 10 Dec 2024
Topological Representations of Heterogeneous Learning Dynamics of Recurrent Spiking Neural Networks Biswadeep Chakraborty Saibal Mukhopadhyay 19 3 0 19 Mar 2024
Learning in Feedback-driven Recurrent Spiking Neural Networks using full-FORCE Training A. Paul Stefan Sylvius Wagner Anup Das 25 7 0 26 May 2022
A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection Biswadeep Chakraborty Xueyuan She Saibal Mukhopadhyay 35 50 0 21 Apr 2021
Long short-term memory and learning-to-learn in networks of spiking neurons G. Bellec Darjan Salaj Anand Subramoney R. Legenstein Wolfgang Maass 111 477 0 26 Mar 2018