Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2202.03133
Cited By
Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?
31 January 2022
Youngeun Kim
Hyoungseob Park
Abhishek Moitra
Abhiroop Bhattacharjee
Yeshwanth Venkatesha
Priyadarshini Panda
AAML
MQ
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?"
4 / 4 papers shown
Title
SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks
Abhishek Moitra
Abhiroop Bhattacharjee
Runcong Kuang
Gokul Krishnan
Yu Cao
Priyadarshini Panda
8
20
0
24 Oct 2022
Toward Robust Spiking Neural Network Against Adversarial Perturbation
Ling Liang
Kaidi Xu
Xing Hu
Lei Deng
Yuan Xie
AAML
18
13
0
12 Apr 2022
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation
Nitin Rathi
G. Srinivasan
Priyadarshini Panda
Kaushik Roy
116
292
0
04 May 2020
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations
Saima Sharmin
Nitin Rathi
Priyadarshini Panda
Kaushik Roy
AAML
106
85
0
23 Mar 2020
1