A Survey of Inductive Biases for Factorial Representation-Learning

15 December 2016

Papers citing "A Survey of Inductive Biases for Factorial Representation-Learning"

45 / 45 papers shown

Title
Transferring disentangled representations: bridging the gap between synthetic and real images Jacopo Dapueto Nicoletta Noceti Francesca Odone OOD 110 0 0 26 Sep 2024
Defining and Measuring Disentanglement for non-Independent Factors of Variation Antonio Almudévar Alfonso Ortega Luis Vicente A. Miguel Eduardo Lleida CoGe DRL 73 1 0 13 Aug 2024
LatentExplainer: Explaining Latent Representations in Deep Generative Models with Multimodal Large Language Models Mengdan Zhu Raasikh Kanjiani Jiahui Lu Andrew Choi Qirui Ye Liang Zhao DiffM 92 1 0 21 Jun 2024
SODA: Bottleneck Diffusion Models for Representation Learning Drew A. Hudson Daniel Zoran Mateusz Malinowski Andrew Kyle Lampinen Andrew Jaegle James L. McClelland Loic Matthey Felix Hill Alexander Lerchner DiffM 106 56 0 29 Nov 2023
Are We Using Autoencoders in a Wrong Way? Gabriele Martino Davide Moroni M. Martinelli 33 1 0 04 Sep 2023
Disentanglement via Latent Quantization Kyle Hsu W. Dorrell James C. R. Whittington Jiajun Wu Chelsea Finn DRL 163 27 0 28 May 2023
An Empirical Study on Clustering Pretrained Embeddings: Is Deep Strictly Better? Tyler R. Scott Ting Liu Michael C. Mozer Andrew C. Gallagher CVBM FedML 68 1 0 09 Nov 2022
$β$ -CapsNet: Learning Disentangled Representation for CapsNet by Information Bottleneck Ming-fei Hu Jian Liu SSL 79 1 0 12 Sep 2022
Controllable Data Generation by Deep Learning: A Review Shiyu Wang Yuanqi Du Xiaojie Guo Bo Pan Zhaohui Qin Liang Zhao 101 28 0 19 Jul 2022
Disentangling Autoencoders (DAE) Jaehoon Cha Jeyan Thiyagalingam CoGe 83 1 0 20 Feb 2022
Investigating Explainability of Generative AI for Code through Scenario-based Design Jiao Sun Q. V. Liao Michael J. Muller Mayank Agarwal Stephanie Houde Kartik Talamadupula Justin D. Weisz 83 165 0 10 Feb 2022
GANSlider: How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Information Hai Dang Lukas Mecke Daniel Buschek 69 34 0 02 Feb 2022
DAReN: A Collaborative Approach Towards Reasoning And Disentangling Pritish Sahu Kalliopi Basioti Vladimir Pavlovic 68 1 0 27 Sep 2021
Invariance-based Multi-Clustering of Latent Space Embeddings for Equivariant Learning Minh Nguyen A. Roy Haoran Zhang BDL DRL 102 1 0 25 Jul 2021
VDSM: Unsupervised Video Disentanglement with State-Space Modeling and Deep Mixtures of Experts M. Vowels Necati Cihan Camgöz Richard Bowden CoGe 87 8 0 12 Mar 2021
On Disentanglement in Gaussian Process Variational Autoencoders Simon Bing Vincent Fortuin Gunnar Rätsch CML CoGe BDL DRL 81 9 0 10 Feb 2021
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement A. Ross Finale Doshi-Velez DRL 84 13 0 09 Feb 2021
Evaluating the Interpretability of Generative Models by Interactive Reconstruction A. Ross Nina Chen Elisa Zhao Hang Elena L. Glassman Finale Doshi-Velez 158 49 0 02 Feb 2021
Measuring Disentanglement: A Review of Metrics M. Carbonneau Julian Zaïdi Jonathan Boilard G. Gagnon CoGe DRL 89 85 0 16 Dec 2020
Disentangled Information Bottleneck Ziqi Pan Li Niu Jianfu Zhang Liqing Zhang 73 37 0 14 Dec 2020
Disentangling Action Sequences: Discovering Correlated Samples Jiantao Wu Lin Wang CML CoGe DRL 13 0 0 17 Oct 2020
Surrogate Model For Field Optimization Using Beta-VAE Based Regression Ajitabh Kumar 48 0 0 26 Aug 2020
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding David A. Klindt Lukas Schott Yash Sharma Ivan Ustyuzhaninov Wieland Brendel Matthias Bethge Dylan M. Paiton CML 148 134 0 21 Jul 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks Yaniv Yacoby Weiwei Pan Finale Doshi-Velez CML DRL 106 26 0 14 Jul 2020
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology Sharon Zhou E. Zelikman F. Lu A. Ng Gunnar Carlsson Stefano Ermon DRL 69 27 0 05 Jun 2020
Adversarial Latent Autoencoders Stanislav Pidhorskyi Donald Adjeroh Gianfranco Doretto GAN DRL 97 261 0 09 Apr 2020
Learning Group Structure and Disentangled Representations of Dynamical Environments Robin Quessard Thomas D. Barrett W. Clements DRL 61 21 0 17 Feb 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 282 321 0 07 Feb 2020
Toward a Controllable Disentanglement Network Zengjie Song Oluwasanmi Koyejo Jiangshe Zhang DRL 41 3 0 22 Jan 2020
Learning Controllable Disentangled Representations with Decorrelation Regularization Zengjie Song Oluwasanmi Koyejo Jiangshe Zhang 47 1 0 25 Dec 2019
Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning Cong Hu Zhenhua Feng Xiaojun Wu J. Kittler CVBM GAN DRL 48 11 0 19 Sep 2019
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations Jan Stühmer Richard Turner Sebastian Nowozin DRL BDL CoGe 198 25 0 05 Sep 2019
Theory and Evaluation Metrics for Learning Disentangled Representations Kien Do T. Tran CoGe DRL 76 96 0 26 Aug 2019
Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders Yin-Jyun Luo Kat R. Agres Dorien Herremans 103 46 0 19 Jun 2019
Generative Restricted Kernel Machines: A Framework for Multi-view Generation and Disentangled Feature Learning Arun Pandey J. Schreurs Johan A. K. Suykens 80 13 0 19 Jun 2019
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs Zinan Lin K. K. Thekumparampil Giulia Fanti Sewoong Oh DRL 110 37 0 14 Jun 2019
Affine Variational Autoencoders: An Efficient Approach for Improving Generalization and Robustness to Distribution Shift Rene Bidart A. Wong DRL OOD 31 5 0 13 May 2019
Variational Autoencoders Pursue PCA Directions (by Accident) Michal Rolínek Dominik Zietlow Georg Martius OOD DRL 78 153 0 17 Dec 2018
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 910 10,632 0 12 Dec 2018
InfoCatVAE: Representation Learning with Categorical Variational Autoencoders Edouard Pineau Marc Lelarge DRL 83 13 0 20 Jun 2018
Understanding disentangling in $β$ -VAE Christopher P. Burgess I. Higgins Arka Pal Loic Matthey Nicholas Watters Guillaume Desjardins Alexander Lerchner CoGe DRL 73 832 0 10 Apr 2018
Learning beyond datasets: Knowledge Graph Augmented Neural Networks for Natural language Processing K. Annervaz Somnath Basu Roy Chowdhury Ambedkar Dukkipati GNN 86 73 0 16 Feb 2018
Isolating Sources of Disentanglement in Variational Autoencoders T. Chen Xuechen Li Roger C. Grosse David Duvenaud DRL 96 445 0 14 Feb 2018
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations Abhishek Kumar P. Sattigeri Avinash Balakrishnan BDL DRL 123 523 0 02 Nov 2017
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning I. Higgins Arka Pal Andrei A. Rusu Loic Matthey Christopher P. Burgess Alexander Pritzel M. Botvinick Charles Blundell Alexander Lerchner DRL 173 417 0 26 Jul 2017