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. 2109.01262
  4. Cited By
On the Accuracy of Analog Neural Network Inference Accelerators

On the Accuracy of Analog Neural Network Inference Accelerators

3 September 2021
T. Xiao
Ben Feinberg
C. Bennett
V. Prabhakar
Prashant Saxena
V. Agrawal
S. Agarwal
M. Marinella
ArXivPDFHTML

Papers citing "On the Accuracy of Analog Neural Network Inference Accelerators"

4 / 4 papers shown
Title
NeuroSim V1.5: Improved Software Backbone for Benchmarking Compute-in-Memory Accelerators with Device and Circuit-level Non-idealities
NeuroSim V1.5: Improved Software Backbone for Benchmarking Compute-in-Memory Accelerators with Device and Circuit-level Non-idealities
James Read
Ming-Yen Lee
Wei-Hsing Huang
Yuan-Chun Luo
A. Lu
Shimeng Yu
34
0
0
05 May 2025
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling
Matthew Burns
Qingyuan Hou
Michael Huang
134
1
0
08 Oct 2024
Towards Green AI: Current status and future research
Towards Green AI: Current status and future research
Christian Clemm
Lutz Stobbe
Kishan Wimalawarne
Jan Druschke
47
2
0
01 May 2024
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
950
20,567
0
17 Apr 2017
1