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. 2312.04752
  4. Cited By
A Test-Time Learning Approach to Reparameterize the Geophysical Inverse
  Problem with a Convolutional Neural Network
v1v2 (latest)

A Test-Time Learning Approach to Reparameterize the Geophysical Inverse Problem with a Convolutional Neural Network

7 December 2023
Anran Xu
L. Heagy
ArXiv (abs)PDFHTML

Papers citing "A Test-Time Learning Approach to Reparameterize the Geophysical Inverse Problem with a Convolutional Neural Network"

2 / 2 papers shown
Title
Towards Understanding the Benefits of Neural Network Parameterizations in Geophysical Inversions: A Study With Neural Fields
Towards Understanding the Benefits of Neural Network Parameterizations in Geophysical Inversions: A Study With Neural Fields
Anran Xu
L. Heagy
134
0
0
21 Mar 2025
Multi-Parameter Molecular MRI Quantification using Physics-Informed Self-Supervised Learning
Multi-Parameter Molecular MRI Quantification using Physics-Informed Self-Supervised Learning
Alex Finkelstein
Nikita Vladimirov
Moritz Zaiss
O. Perlman
119
2
0
10 Nov 2024
1