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. 2304.04781
  4. Cited By
An autoencoder compression approach for accelerating large-scale inverse
  problems

An autoencoder compression approach for accelerating large-scale inverse problems

10 April 2023
J. Wittmer
Jacob Badger
H. Sundar
T. Bui-Thanh
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "An autoencoder compression approach for accelerating large-scale inverse problems"

16 / 16 papers shown
Title
Symmetry-Aware Autoencoders: s-PCA and s-nlPCA
Symmetry-Aware Autoencoders: s-PCA and s-nlPCA
Simon Kneer
T. Sayadi
D. Sipp
Peter J. Schmid
Georgios Rigas
42
10
0
04 Nov 2021
Closing the "Quantum Supremacy" Gap: Achieving Real-Time Simulation of a
  Random Quantum Circuit Using a New Sunway Supercomputer
Closing the "Quantum Supremacy" Gap: Achieving Real-Time Simulation of a Random Quantum Circuit Using a New Sunway Supercomputer
Yong
Xin Liu
Xin
Liu
Fang Li
...
Huarong Chen
Chu Guo
Heliang Huang
Wenzhao Wu
Dexun Chen
LRM
44
136
0
27 Oct 2021
Exploring Autoencoder-based Error-bounded Compression for Scientific
  Data
Exploring Autoencoder-based Error-bounded Compression for Scientific Data
Jinyang Liu
Sheng Di
Kai Zhao
Sian Jin
Dingwen Tao
Xin Liang
Zizhong Chen
Franck Cappello
63
49
0
25 May 2021
Better Latent Spaces for Better Autoencoders
Better Latent Spaces for Better Autoencoders
B. Dillon
Tilman Plehn
C. Sauer
P. Sorrenson
BDLDRL
49
55
0
16 Apr 2021
An autoencoder-based reduced-order model for eigenvalue problems with
  application to neutron diffusion
An autoencoder-based reduced-order model for eigenvalue problems with application to neutron diffusion
Toby R. F. Phillips
Claire E. Heaney
Paul N. Smith
Christopher C. Pain
45
59
0
15 Aug 2020
SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost
  Computation
SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation
Yang Zhao
Xiaohan Chen
Yue Wang
Chaojian Li
Haoran You
Y. Fu
Yuan Xie
Zhangyang Wang
Yingyan Lin
MQ
95
43
0
07 May 2020
Demystifying the Performance of HPC Scientific Applications on NVM-based
  Memory Systems
Demystifying the Performance of HPC Scientific Applications on NVM-based Memory Systems
Ivy Bo Peng
Kai Wu
Jie Ren
Dong Li
Maya Gokhale
48
19
0
16 Feb 2020
Solving Bayesian Inverse Problems via Variational Autoencoders
Solving Bayesian Inverse Problems via Variational Autoencoders
Hwan Goh
Sheroze Sheriffdeen
J. Wittmer
T. Bui-Thanh
BDL
112
39
0
05 Dec 2019
A PCA-like Autoencoder
A PCA-like Autoencoder
Saïd Ladjal
A. Newson
Chi-Hieu Pham
60
33
0
02 Apr 2019
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
Yang You
Jing Li
Sashank J. Reddi
Jonathan Hseu
Sanjiv Kumar
Srinadh Bhojanapalli
Xiaodan Song
J. Demmel
Kurt Keutzer
Cho-Jui Hsieh
ODL
267
999
0
01 Apr 2019
From Principal Subspaces to Principal Components with Linear
  Autoencoders
From Principal Subspaces to Principal Components with Linear Autoencoders
Elad Plaut
SSL
56
115
0
26 Apr 2018
Deep Convolutional AutoEncoder-based Lossy Image Compression
Deep Convolutional AutoEncoder-based Lossy Image Compression
Zhengxue Cheng
Heming Sun
Masaru Takeuchi
J. Katto
49
180
0
25 Apr 2018
Trading Computation for Communication: A Taxonomy
Trading Computation for Communication: A Taxonomy
Ismail Akturk
Ulya R. Karpuzcu
17
6
0
18 Sep 2017
Early Evaluation of Intel Optane Non-Volatile Memory with HPC I/O
  Workloads
Early Evaluation of Intel Optane Non-Volatile Memory with HPC I/O Workloads
Kai Wu
Frank Ober
Shari Hamlin
Dong Li
20
23
0
07 Aug 2017
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
455
16,923
0
20 Dec 2013
A computational framework for infinite-dimensional Bayesian inverse
  problems. Part I: The linearized case, with application to global seismic
  inversion
A computational framework for infinite-dimensional Bayesian inverse problems. Part I: The linearized case, with application to global seismic inversion
T. Bui-Thanh
Omar Ghattas
James Martin
G. Stadler
84
392
0
06 Aug 2013
1