9 citations · 18 across the 6 of their papers we have counts for
6 papers
In-Hardware Learning of Multilayer Spiking Neural Networks on a Neuromorphic Processor
Amar Shrestha, Haowen Fang, Daniel Patrick Rider +2
Although widely used in machine learning, backpropagation cannot directly be applied to SNN training and is not feasible on a neuromorphic processor that emulates biological neuron…
Multivariate Time Series Classification Using Spiking Neural Networks
Haowen Fang, Amar Shrestha, Qinru Qiu
There is an increasing demand to process streams of temporal data in energy-limited scenarios such as embedded devices, driven by the advancement and expansion of Internet of Thing…
MAGNet: Multi-Region Attention-Assisted Grounding of Natural Language Queries at Phrase Level
Amar Shrestha, Krittaphat Pugdeethosapol, Haowen Fang +1
Grounding free-form textual queries necessitates an understanding of these textual phrases and its relation to the visual cues to reliably reason about the described locations. Spa…
Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network
Haowen Fang, Amar Shrestha, Ziyi Zhao +1
The recent discovered spatial-temporal information processing capability of bio-inspired Spiking neural networks (SNN) has enabled some interesting models and applications. However…
High-Level Plan for Behavioral Robot Navigation with Natural Language Directions and R-NET
Amar Shrestha, Krittaphat Pugdeethosapol, Haowen Fang +1
When the navigational environment is known, it can be represented as a graph where landmarks are nodes, the robot behaviors that move from node to node are edges, and the route is…
Scalable NoC-based Neuromorphic Hardware Learning and Inference
Haowem Fang, Amar Shrestha, De Ma +1
Bio-inspired neuromorphic hardware is a research direction to approach brain's computational power and energy efficiency. Spiking neural networks (SNN) encode information as sparse…