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. 2010.03954
  4. Cited By
A Survey on Deep Neural Network Compression: Challenges, Overview, and
  Solutions

A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions

5 October 2020
Rahul Mishra
Hari Prabhat Gupta
Tanima Dutta
ArXivPDFHTML

Papers citing "A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions"

12 / 12 papers shown
Title
Compact Language Models via Pruning and Knowledge Distillation
Compact Language Models via Pruning and Knowledge Distillation
Saurav Muralidharan
Sharath Turuvekere Sreenivas
Raviraj Joshi
Marcin Chochowski
M. Patwary
M. Shoeybi
Bryan Catanzaro
Jan Kautz
Pavlo Molchanov
SyDa
MQ
34
37
0
19 Jul 2024
Compression of Recurrent Neural Networks using Matrix Factorization
Compression of Recurrent Neural Networks using Matrix Factorization
Lucas Maison
Hélion Marie du Mas des Bourboux
Thomas Courtat
13
0
0
19 Oct 2023
Distributed Neural Representation for Reactive in situ Visualization
Distributed Neural Representation for Reactive in situ Visualization
Qi Wu
J. Insley
V. Mateevitsi
S. Rizzi
M. Papka
Kwan-Liu Ma
24
1
0
28 Mar 2023
Designing and Training of Lightweight Neural Networks on Edge Devices
  using Early Halting in Knowledge Distillation
Designing and Training of Lightweight Neural Networks on Edge Devices using Early Halting in Knowledge Distillation
Rahul Mishra
Hari Prabhat Gupta
27
8
0
30 Sep 2022
Graph Neural Networks in IoT: A Survey
Graph Neural Networks in IoT: A Survey
Guimin Dong
Mingyue Tang
Zhiyuan Wang
Jiechao Gao
Sikun Guo
Lihua Cai
Robert Gutierrez
Brad Campbell
Laura E. Barnes
M. Boukhechba
GNN
AI4CE
34
96
0
29 Mar 2022
On Neural Network Equivalence Checking using SMT Solvers
On Neural Network Equivalence Checking using SMT Solvers
Charis Eleftheriadis
Nikolaos Kekatos
Panagiotis Katsaros
S. Tripakis
AAML
21
12
0
22 Mar 2022
Modeling the AC Power Flow Equations with Optimally Compact Neural
  Networks: Application to Unit Commitment
Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment
Alyssa Kody
Samuel C. Chevalier
Spyros Chatzivasileiadis
Daniel Molzahn
62
37
0
21 Oct 2021
MD Loss: Efficient Training of 3D Seismic Fault Segmentation Network
  under Sparse Labels by Weakening Anomaly Annotation
MD Loss: Efficient Training of 3D Seismic Fault Segmentation Network under Sparse Labels by Weakening Anomaly Annotation
Yimin Dou
Kewen Li
Jianbing Zhu
Timing Li
Shaoquan Tan
Zongchao Huang
8
25
0
11 Oct 2021
CHISEL: Compression-Aware High-Accuracy Embedded Indoor Localization
  with Deep Learning
CHISEL: Compression-Aware High-Accuracy Embedded Indoor Localization with Deep Learning
Liping Wang
Saideep Tiku
S. Pasricha
19
32
0
02 Jul 2021
Efficient Deep Learning: A Survey on Making Deep Learning Models
  Smaller, Faster, and Better
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better
Gaurav Menghani
VLM
MedIm
23
365
0
16 Jun 2021
Compacting Deep Neural Networks for Internet of Things: Methods and
  Applications
Compacting Deep Neural Networks for Internet of Things: Methods and Applications
Ke Zhang
Hanbo Ying
Hongning Dai
Lin Li
Yuangyuang Peng
Keyi Guo
Hongfang Yu
16
38
0
20 Mar 2021
What is the State of Neural Network Pruning?
What is the State of Neural Network Pruning?
Davis W. Blalock
Jose Javier Gonzalez Ortiz
Jonathan Frankle
John Guttag
188
1,027
0
06 Mar 2020
1