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. 1911.00234
  4. Cited By
Active$^2$ Learning: Actively reducing redundancies in Active Learning
  methods for Sequence Tagging and Machine Translation

Active2^22 Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation

1 November 2019
Rishi Hazra
Parag Dutta
Shubham Gupta
Mohammed Abdul Qaathir
Ambedkar Dukkipati
    VLM
ArXivPDFHTML

Papers citing "Active$^2$ Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation"

1 / 1 papers shown
Title
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,167
0
06 Jun 2015
1