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Disentangling by Factorising

16 February 2018

Papers citing "Disentangling by Factorising"

50 / 790 papers shown

Title
Learning Sampling in Financial Statement Audits using Vector Quantised Autoencoder Neural Networks Marco Schreyer Timur Sattarov Anita Gierbl Bernd Reimer Damian Borth DRL 32 3 0 06 Aug 2020
Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification Nan Pu Wei Chen Yu Liu E. Bakker M. Lew DRL 63 87 0 06 Aug 2020
The pursuit of beauty: Converting image labels to meaningful vectors S. Karatsiolis A. Kamilaris 25 0 0 03 Aug 2020
dMelodies: A Music Dataset for Disentanglement Learning Ashis Pati Francesco Ferroni Alexander Lerch CoGe DRL 58 10 0 29 Jul 2020
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 130 58 0 29 Jul 2020
Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling Hao Hao Tan Dorien Herremans MGen 60 74 0 29 Jul 2020
A Commentary on the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD DRL 86 21 0 28 Jul 2020
Data-efficient visuomotor policy training using reinforcement learning and generative models Ali Ghadirzadeh Petra Poklukar Ville Kyrki Danica Kragic Mårten Björkman OffRL 109 9 0 26 Jul 2020
MRGAN: Multi-Rooted 3D Shape Generation with Unsupervised Part Disentanglement Rinon Gal Amit H. Bermano Hao Zhang Daniel Cohen-Or 3DPC 65 18 0 25 Jul 2020
Learning Disentangled Representations with Latent Variation Predictability Xinqi Zhu Chang Xu Dacheng Tao CoGe DRL 78 27 0 25 Jul 2020
Unsupervised Shape and Pose Disentanglement for 3D Meshes Keyang Zhou Bharat Lal Bhatnagar Gerard Pons-Moll 3DH DRL 58 78 0 22 Jul 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 146 134 0 21 Jul 2020
Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective Ruixiang Zhang Masanori Koyama Katsuhiko Ishiguro CML 56 6 0 21 Jul 2020
Learning latent representations across multiple data domains using Lifelong VAEGAN Fei Ye A. Bors SyDa CLL 68 67 0 20 Jul 2020
Mixture Representation Learning with Coupled Autoencoders Yeganeh M. Marghi Rohan Gala U. Sümbül BDL 14 0 0 20 Jul 2020
Unsupervised Controllable Generation with Self-Training Grigorios G. Chrysos Jean Kossaifi Zhiding Yu Anima Anandkumar GAN 37 4 0 17 Jul 2020
Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters Haoyun Liang Zhihao Ouyang Yuyuan Zeng Hang Su Zihao He Shutao Xia Jun Zhu Bo Zhang 92 47 0 16 Jul 2020
PRI-VAE: Principle-of-Relevant-Information Variational Autoencoders Yanjun Li Shujian Yu José C. Príncipe Xiaolin Li D. Wu DRL 58 7 0 13 Jul 2020
README: REpresentation learning by fairness-Aware Disentangling MEthod Sungho Park D. Kim Sunhee Hwang H. Byun DRL CML 70 18 0 07 Jul 2020
Benefiting Deep Latent Variable Models via Learning the Prior and Removing Latent Regularization Rogan Morrow Wei-Chen Chiu DRL 31 0 0 07 Jul 2020
Decoder-free Robustness Disentanglement without (Additional) Supervision Yifei Wang Dan Peng Furui Liu Zhenguo Li Zhitang Chen Jiansheng Yang AAML 29 1 0 02 Jul 2020
Swapping Autoencoder for Deep Image Manipulation Taesung Park Jun-Yan Zhu Oliver Wang Jingwan Lu Eli Shechtman Alexei A. Efros Richard Y. Zhang 142 337 0 01 Jul 2020
Neural Decomposition: Functional ANOVA with Variational Autoencoders Kaspar Märtens C. Yau DRL 23 10 0 25 Jun 2020
Generative causal explanations of black-box classifiers Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 96 73 0 24 Jun 2020
Disentangling by Subspace Diffusion David Pfau I. Higgins Aleksandar Botev S. Racanière DiffM DRL 79 37 0 23 Jun 2020
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information Pengyu Cheng Weituo Hao Shuyang Dai Jiachang Liu Zhe Gan Lawrence Carin VLM 98 359 0 22 Jun 2020
Capturing Label Characteristics in VAEs Thomas Joy Sebastian M. Schmon Philip Torr N. Siddharth Tom Rainforth CML DRL 97 47 0 17 Jun 2020
Contrastive Learning for Weakly Supervised Phrase Grounding Tanmay Gupta Arash Vahdat Gal Chechik Xiaodong Yang Jan Kautz Derek Hoiem ObjD SSL 163 144 0 17 Jun 2020
Fine-grained Sentiment Controlled Text Generation Bidisha Samanta Mohit Agarwal Niloy Ganguly 44 4 0 17 Jun 2020
On Disentangled Representations Learned From Correlated Data Frederik Trauble Elliot Creager Niki Kilbertus Francesco Locatello Andrea Dittadi Anirudh Goyal Bernhard Schölkopf Stefan Bauer OOD CML 86 117 0 14 Jun 2020
PCAAE: Principal Component Analysis Autoencoder for organising the latent space of generative networks Chi-Hieu Pham Saïd Ladjal A. Newson DRL 96 33 0 14 Jun 2020
Structure by Architecture: Structured Representations without Regularization Felix Leeb Giulia Lanzillotta Yashas Annadani M. Besserve Stefan Bauer Bernhard Schölkopf OOD CML 89 8 0 14 Jun 2020
An Improved Semi-Supervised VAE for Learning Disentangled Representations Weili Nie Zichao Wang Ankit B. Patel Richard G. Baraniuk CoGe DRL 61 4 0 12 Jun 2020
Learning Diverse Representations for Fast Adaptation to Distribution Shift Daniel Pace A. Russo Murray Shanahan OOD 76 2 0 12 Jun 2020
Disentangled Representation Learning and Generation with Manifold Optimization Arun Pandey Michaël Fanuel J. Schreurs Johan A. K. Suykens CoGe DRL 39 23 0 12 Jun 2020
Longitudinal Self-Supervised Learning Qingyu Zhao Zixuan Liu Ehsan Adeli K. Pohl 68 30 0 12 Jun 2020
DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors Sarthak Bhagat Vishaal Udandarao Shagun Uppal CoGe SSL DRL 60 6 0 10 Jun 2020
Deep Dimension Reduction for Supervised Representation Learning Jian Huang Yuling Jiao Xu Liao Jin Liu Zhou Yu DRL 46 16 0 10 Jun 2020
To Regularize or Not To Regularize? The Bias Variance Trade-off in Regularized AEs A. Mondal Himanshu Asnani Parag Singla A. Prathosh DRL 35 1 0 10 Jun 2020
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement Xiaojie Guo Liang Zhao Zhao Qin Lingfei Wu Amarda Shehu Yanfang Ye CoGe DRL 123 46 0 09 Jun 2020
Deep active inference agents using Monte-Carlo methods Zafeirios Fountas Noor Sajid P. Mediano Karl J. Friston 119 106 0 07 Jun 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
Nested Scale Editing for Conditional Image Synthesis Lingzhi Zhang Jiancong Wang Yinshuang Xu Jie Min Tarmily Wen J. Gee Jianbo Shi DiffM 72 3 0 03 Jun 2020
Variational Mutual Information Maximization Framework for VAE Latent Codes with Continuous and Discrete Priors Andriy Serdega Dae-Shik Kim DRL 32 0 0 02 Jun 2020
VMI-VAE: Variational Mutual Information Maximization Framework for VAE With Discrete and Continuous Priors Andriy Serdega Dae-Shik Kim DRL 39 4 0 28 May 2020
VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics Zichao Wang Yi Gu Andrew Lan Richard Baraniuk 57 10 0 27 May 2020
Contrastive Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised Learning of Disentangled Speech Representations Janek Ebbers Michael Kuhlmann Tobias Cord-Landwehr Reinhold Haeb-Umbach DRL CoGe SSL 58 4 0 26 May 2020
S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation Yizhe Zhu Martin Renqiang Min Asim Kadav H. Graf CoGe DRL 78 97 0 23 May 2020
Adversarial Canonical Correlation Analysis B. Dutton CML AAML 6 0 0 20 May 2020
Face Identity Disentanglement via Latent Space Mapping Yotam Nitzan Amit H. Bermano Yangyan Li Daniel Cohen-Or CVBM CoGe DRL 140 16 0 15 May 2020