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. 2207.00200
  4. Cited By
Studying the impact of magnitude pruning on contrastive learning methods

Studying the impact of magnitude pruning on contrastive learning methods

1 July 2022
Francesco Corti
R. Entezari
Sara Hooker
D. Bacciu
O. Saukh
ArXivPDFHTML

Papers citing "Studying the impact of magnitude pruning on contrastive learning methods"

2 / 2 papers shown
Title
REDS: Resource-Efficient Deep Subnetworks for Dynamic Resource
  Constraints
REDS: Resource-Efficient Deep Subnetworks for Dynamic Resource Constraints
Francesco Corti
Balz Maag
Joachim Schauer
U. Pferschy
O. Saukh
49
2
0
22 Nov 2023
Relating tSNE and UMAP to Classical Dimensionality Reduction
Relating tSNE and UMAP to Classical Dimensionality Reduction
Andrew Draganov
Simon Dohn
FAtt
34
4
0
20 Jun 2023
1