ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1906.02796
  4. Cited By
Stochasticity and Robustness in Spiking Neural Networks

Stochasticity and Robustness in Spiking Neural Networks

6 June 2019
W. Olin-Ammentorp
K. Beckmann
Catherine D. Schuman
J. Plank
N. Cady
ArXivPDFHTML

Papers citing "Stochasticity and Robustness in Spiking Neural Networks"

4 / 4 papers shown
Title
On the Privacy-Preserving Properties of Spiking Neural Networks with Unique Surrogate Gradients and Quantization Levels
On the Privacy-Preserving Properties of Spiking Neural Networks with Unique Surrogate Gradients and Quantization Levels
Ayana Moshruba
Shay Snyder
Hamed Poursiami
Maryam Parsa
AAML
71
2
0
25 Feb 2025
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects
  of Discrete Input Encoding and Non-Linear Activations
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
116
86
0
23 Mar 2020
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
335
5,849
0
08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,167
0
06 Jun 2015
1