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. 2408.17363
  4. Cited By
Look, Learn and Leverage (L$^3$): Mitigating Visual-Domain Shift and
  Discovering Intrinsic Relations via Symbolic Alignment

Look, Learn and Leverage (L3^33): Mitigating Visual-Domain Shift and Discovering Intrinsic Relations via Symbolic Alignment

30 August 2024
Hanchen Xie
Jiageng Zhu
Mahyar Khayatkhoei
Jiazhi Li
Wael AbdAlmageed
    OOD
ArXivPDFHTML

Papers citing "Look, Learn and Leverage (L$^3$): Mitigating Visual-Domain Shift and Discovering Intrinsic Relations via Symbolic Alignment"

2 / 2 papers shown
Title
Weakly-Supervised Disentanglement Without Compromises
Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello
Ben Poole
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
Michael Tschannen
CoGe
OOD
DRL
184
313
0
07 Feb 2020
A Compositional Object-Based Approach to Learning Physical Dynamics
A Compositional Object-Based Approach to Learning Physical Dynamics
Michael Chang
T. Ullman
Antonio Torralba
J. Tenenbaum
AI4CE
OCL
241
438
0
01 Dec 2016
1