Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective

14 June 2021

Papers citing "Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective"

8 / 8 papers shown

Title
Negate or Embrace: On How Misalignment Shapes Multimodal Representation Learning Yichao Cai Yuhang Liu Erdun Gao T. Jiang Zhen Zhang Anton van den Hengel J. Shi 62 0 0 14 Apr 2025
Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach Sagar Shrestha Xiao Fu 23 3 0 18 Jan 2024
Causal Representation Learning Made Identifiable by Grouping of Observational Variables H. Morioka Aapo Hyvarinen OOD CML BDL 33 9 0 24 Oct 2023
Provable Subspace Identification Under Post-Nonlinear Mixtures Qi Lyu Xiao Fu CoGe 21 0 0 14 Oct 2022
Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann Yash Sharma Steffen Schneider Matthias Bethge Wieland Brendel SSL 238 207 0 17 Feb 2021
Understanding self-supervised Learning Dynamics without Contrastive Pairs Yuandong Tian Xinlei Chen Surya Ganguli SSL 138 279 0 12 Feb 2021
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 178 313 0 07 Feb 2020
A Multi-View Embedding Space for Modeling Internet Images, Tags, and their Semantics Yunchao Gong Qifa Ke Michael Isard Svetlana Lazebnik 3DV 65 584 0 18 Dec 2012