1 citations · 2 across the 5 of their papers we have counts for
6 papers
TSkips: Efficiency Through Explicit Temporal Delay Connections in Spiking Neural Networks
Prajna G. Malettira, Shubham Negi, Wachirawit Ponghiran +1
Spiking Neural Networks (SNNs) with their bio-inspired Leaky Integrate-and-Fire (LIF) neurons inherently capture temporal information. This makes them well-suited for sequential ta…
FEDORA: Flying Event Dataset fOr Reactive behAvior
Amogh Joshi, Adarsh Kosta, Wachirawit Ponghiran +2
The ability of resource-constrained biological systems such as fruitflies to perform complex and high-speed maneuvers in cluttered environments has been one of the prime sources of…
Event-based Temporally Dense Optical Flow Estimation with Sequential Learning
Wachirawit Ponghiran, Chamika Mihiranga Liyanagedera, Kaushik Roy
Event cameras provide an advantage over traditional frame-based cameras when capturing fast-moving objects without a motion blur. They achieve this by recording changes in light in…
Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning
Wachirawit Ponghiran, Kaushik Roy
Spiking neural networks (SNNs) with leaky integrate and fire (LIF) neurons, can be operated in an event-driven manner and have internal states to retain information over time, prov…
Reinforcement Learning with Low-Complexity Liquid State Machines
Wachirawit Ponghiran, Gopalakrishnan Srinivasan, Kaushik Roy
We propose reinforcement learning on simple networks consisting of random connections of spiking neurons (both recurrent and feed-forward) that can learn complex tasks with very li…
A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks
Saima Sharmin, Priyadarshini Panda, Syed Shakib Sarwar +3
In this era of machine learning models, their functionality is being threatened by adversarial attacks. In the face of this struggle for making artificial neural networks robust, f…