Nonlinear Independent Component Analysis for Principled Disentanglement in Unsupervised Deep Learning

29 March 2023

Papers citing "Nonlinear Independent Component Analysis for Principled Disentanglement in Unsupervised Deep Learning"

7 / 7 papers shown

Title
Analyzing Generative Models by Manifold Entropic Metrics Daniel Galperin Ullrich Köthe DRL 16 0 0 25 Oct 2024
Unsupervised Representation Learning from Sparse Transformation Analysis Yue Song Thomas Anderson Keller Yisong Yue Pietro Perona Max Welling DRL 29 0 0 07 Oct 2024
A Review of Change of Variable Formulas for Generative Modeling Ullrich Kothe 19 6 0 04 Aug 2023
Identifiability of latent-variable and structural-equation models: from linear to nonlinear Aapo Hyvarinen Ilyes Khemakhem R. Monti CML 25 41 0 06 Feb 2023
Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann Yash Sharma Steffen Schneider Matthias Bethge Wieland Brendel SSL 236 207 0 17 Feb 2021
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 137 656 0 28 Dec 2020
Multi-task self-supervised learning for Robust Speech Recognition Mirco Ravanelli Jianyuan Zhong Santiago Pascual P. Swietojanski João Monteiro J. Trmal Yoshua Bengio SSL 171 288 0 25 Jan 2020