Toward the Identifiability of Comparative Deep Generative Models

29 January 2024

Papers citing "Toward the Identifiability of Comparative Deep Generative Models"

9 / 9 papers shown

Title
Contrastive independent component analysis Kexin Wang Aida Maraj A. Seigal CML 55 1 0 02 Jul 2024
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 75 60 0 01 Jun 2023
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez Natavsa Tagasovska Stephen Ra K. Cho J. Pritchard Aviv Regev OOD CML DRL 53 35 0 07 Nov 2022
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA Sébastien Lachapelle Pau Rodríguez López Yash Sharma Katie Everett Rémi Le Priol Alexandre Lacoste Simon Lacoste-Julien CML OOD 65 137 0 21 Jul 2021
Probabilistic Contrastive Principal Component Analysis Didong Li Andrew Jones Barbara E. Engelhardt 43 17 0 14 Dec 2020
Dynamical Variational Autoencoders: A Comprehensive Review Laurent Girin Simon Leglaive Xiaoyu Bie Julien Diard Thomas Hueber Xavier Alameda-Pineda BDL 52 213 0 28 Aug 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 274 42,038 0 03 Dec 2019
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems Tianyi Lin Chi Jin Michael I. Jordan 80 505 0 02 Jun 2019
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 44 1,336 0 16 Feb 2018