Variational Inference of Disentangled Latent Concepts from Unlabeled Observations

2 November 2017

Papers citing "Variational Inference of Disentangled Latent Concepts from Unlabeled Observations"

50 / 132 papers shown

Title
Analyzing Generative Models by Manifold Entropic Metrics Daniel Galperin Ullrich Köthe DRL 28 0 0 25 Oct 2024
Unsupervised Representation Learning from Sparse Transformation Analysis Yue Song Thomas Anderson Keller Yisong Yue Pietro Perona Max Welling DRL 36 0 0 07 Oct 2024
Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models Baao Xie Qiuyu Chen Yunnan Wang Zequn Zhang Xin Jin Wenjun Zeng OffRL 43 2 0 26 Jul 2024
MAGIC: Modular Auto-encoder for Generalisable Model Inversion with Bias Corrections Yihang She Clement Atzberger Andrew Blake Adriano Gualandi Srinivasan Keshav AI4CE 30 1 0 29 May 2024
DualContrast: Unsupervised Disentangling of Content and Transformations with Implicit Parameterization M. R. Uddin Min Xu 51 0 0 27 May 2024
Towards Controllable Time Series Generation Yifan Bao Yihao Ang Qiang Huang Anthony K. H. Tung Zhiyong Huang DiffM 46 4 0 06 Mar 2024
From Spectra to Biophysical Insights: End-to-End Learning with a Biased Radiative Transfer Model Yihang She Clement Atzberger Andrew Blake Srinivasan Keshav 27 0 0 05 Mar 2024
Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning Ruiqian Nai Zixin Wen Ji Li Yuanzhi Li Yang Gao 46 2 0 01 Mar 2024
Sound Source Separation Using Latent Variational Block-Wise Disentanglement Karim Helwani M. Togami Paris Smaragdis Michael M. Goodwin BDL DRL 26 1 0 08 Feb 2024
CFASL: Composite Factor-Aligned Symmetry Learning for Disentanglement in Variational AutoEncoder Heeseung Jung Jaehyoung Jeong Kangil Kim CoGe 34 0 0 17 Jan 2024
Text Attribute Control via Closed-Loop Disentanglement Lei Sha Thomas Lukasiewicz DRL 45 2 0 01 Dec 2023
Matching aggregate posteriors in the variational autoencoder Surojit Saha Sarang Joshi Ross T. Whitaker DRL 37 4 0 13 Nov 2023
Identifying Semantic Component for Robust Molecular Property Prediction Zijian Li Zunhong Xu Ruichu Cai Zhenhui Yang Yuguang Yan Zhifeng Hao Guan-Hong Chen Kun Zhang 25 9 0 08 Nov 2023
Learning Disentangled Speech Representations Yusuf Brima U. Krumnack Simone Pika Gunther Heidemann CoGe DRL 43 3 0 04 Nov 2023
Subspace Identification for Multi-Source Domain Adaptation Zijian Li Ruichu Cai Guan-Hong Chen Boyang Sun Zhifeng Hao Kun Zhang 36 33 0 07 Oct 2023
Disentanglement Learning via Topology Nikita Balabin Daria Voronkova I. Trofimov Evgeny Burnaev S. Barannikov DRL 60 2 0 24 Aug 2023
Evaluating unsupervised disentangled representation learning for genomic discovery and disease risk prediction T. Yun BDL DRL 14 0 0 17 Jul 2023
A Category-theoretical Meta-analysis of Definitions of Disentanglement Yivan Zhang Masashi Sugiyama 38 3 0 11 May 2023
Rotation and Translation Invariant Representation Learning with Implicit Neural Representations Sehyun Kwon Jooyoung Choi Ernest K. Ryu OOD 41 4 0 27 Apr 2023
How good are variational autoencoders at transfer learning? Lisa Bonheme M. Grzes OOD DRL 23 2 0 21 Apr 2023
TC-VAE: Uncovering Out-of-Distribution Data Generative Factors Cristian Meo Anirudh Goyal Justin Dauwels DRL CoGe CML 27 2 0 08 Apr 2023
Correcting Flaws in Common Disentanglement Metrics Louis Mahon Lei Shah Thomas Lukasiewicz CoGe DRL 42 3 0 05 Apr 2023
Multifactor Sequential Disentanglement via Structured Koopman Autoencoders Nimrod Berman Ilana D Naiman Omri Azencot CoGe 32 22 0 30 Mar 2023
Object-Centric Slot Diffusion Jindong Jiang Fei Deng Gautam Singh S. Ahn DiffM BDL OCL 25 57 0 20 Mar 2023
Measuring axiomatic soundness of counterfactual image models M. Monteiro Fabio De Sousa Ribeiro Nick Pawlowski Daniel Coelho De Castro Ben Glocker 44 25 0 02 Mar 2023
Autocodificadores Variacionales (VAE) Fundamentos Teóricos y Aplicaciones J. D. L. Torre DRL 20 1 0 18 Feb 2023
Disentangling Learning Representations with Density Estimation Eric C. Yeats Frank Liu Hai Helen Li BDL DRL CML 54 2 0 08 Feb 2023
Beyond Statistical Similarity: Rethinking Metrics for Deep Generative Models in Engineering Design Lyle Regenwetter Akash Srivastava Dan Gutfreund Faez Ahmed 24 28 0 06 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality Gaël Gendron Michael Witbrock Gillian Dobbie OOD AI4CE CML 41 13 0 01 Feb 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Erdun Gao Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 57 11 0 29 Jan 2023
ContraFeat: Contrasting Deep Features for Semantic Discovery Xinqi Zhu Chang Xu Dacheng Tao DRL 26 2 0 14 Dec 2022
LADIS: Language Disentanglement for 3D Shape Editing Ian Huang Panos Achlioptas Tianyi Zhang Sergey Tulyakov Minhyuk Sung Leonidas J. Guibas 34 10 0 09 Dec 2022
Disentangled Representation Learning Xin Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 37 78 0 21 Nov 2022
Neural Systematic Binder Gautam Singh Yeongbin Kim Sungjin Ahn OCL 32 36 0 02 Nov 2022
Fast and Efficient Scene Categorization for Autonomous Driving using VAEs Saravanabalagi Ramachandran Jonathan Horgan Ganesh Sistu J. McDonald 3DV 29 1 0 26 Oct 2022
DOT-VAE: Disentangling One Factor at a Time Vaishnavi Patil Matthew Evanusa J. JáJá CoGe DRL CML 23 1 0 19 Oct 2022
Disentanglement of Correlated Factors via Hausdorff Factorized Support Karsten Roth Mark Ibrahim Zeynep Akata Pascal Vincent Diane Bouchacourt CML OOD CoGe 41 33 0 13 Oct 2022
Auto-Encoding Goodness of Fit A. Palmer Zhiyi Chi Derek Aguiar J. Bi 46 1 0 12 Oct 2022
NashAE: Disentangling Representations through Adversarial Covariance Minimization Eric C. Yeats Frank Liu David A. P. Womble Hai Helen Li CML 38 10 0 21 Sep 2022
SW-VAE: Weakly Supervised Learn Disentangled Representation Via Latent Factor Swapping Jiageng Zhu Hanchen Xie Wael AbdAlmageed SSL CoGe DRL 35 4 0 21 Sep 2022
Disentangling Shape and Pose for Object-Centric Deep Active Inference Models Stefano Ferraro Toon Van de Maele Pietro Mazzaglia Tim Verbelen Bart Dhoedt 3DV OCL DRL 34 8 0 16 Sep 2022
Gromov-Wasserstein Autoencoders Nao Nakagawa Ren Togo Takahiro Ogawa Miki Haseyama GAN DRL 26 11 0 15 Sep 2022
Weakly Supervised Invariant Representation Learning Via Disentangling Known and Unknown Nuisance Factors Jiageng Zhu Hanchen Xie Wael AbdAlmageed 32 1 0 15 Sep 2022
Modular Representations for Weak Disentanglement Andrea Valenti D. Bacciu 36 0 0 12 Sep 2022
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks Tilman Raukur A. Ho Stephen Casper Dylan Hadfield-Menell AAML AI4CE 23 124 0 27 Jul 2022
Factorizing Knowledge in Neural Networks Xingyi Yang Jingwen Ye Xinchao Wang MoMe 47 121 0 04 Jul 2022
When are Post-hoc Conceptual Explanations Identifiable? Tobias Leemann Michael Kirchhof Yao Rong Enkelejda Kasneci Gjergji Kasneci 52 10 0 28 Jun 2022
Going Deeper than Tracking: a Survey of Computer-Vision Based Recognition of Animal Pain and Affective States Sofia Broomé Marcelo Feighelstein Anna Zamansky Gabriel Carreira Lencioni P. Andersen Francisca Pessanha M. Mahmoud Hedvig Kjellström A. A. Salah 38 11 0 16 Jun 2022
Embrace the Gap: VAEs Perform Independent Mechanism Analysis Patrik Reizinger Luigi Gresele Jack Brady Julius von Kügelgen Dominik Zietlow Bernhard Schölkopf Georg Martius Wieland Brendel M. Besserve DRL 35 19 0 06 Jun 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 106 64 0 31 May 2022