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Learning Deep Disentangled Embeddings with the F-Statistic Loss

14 February 2018

Papers citing "Learning Deep Disentangled Embeddings with the F-Statistic Loss"

40 / 140 papers shown

Title
Multilinear Latent Conditioning for Generating Unseen Attribute Combinations Markos Georgopoulos Grigorios G. Chrysos Maja Pantic Yannis Panagakis GAN DRL 68 17 0 09 Sep 2020
Measuring the Biases and Effectiveness of Content-Style Disentanglement Xiao Liu Spyridon Thermos Gabriele Valvano A. Chartsias Alison Q. OÑeil Sotirios A. Tsaftaris CoGe DRL 114 18 0 27 Aug 2020
WeLa-VAE: Learning Alternative Disentangled Representations Using Weak Labels Vasilis Margonis Athanasios Davvetas I. Klampanos CoGe DRL CML 40 3 0 22 Aug 2020
Linear Disentangled Representations and Unsupervised Action Estimation Matthew Painter Jonathon S. Hare Adam Prugel-Bennett CoGe DRL 70 20 0 18 Aug 2020
Metric Learning vs Classification for Disentangled Music Representation Learning Jongpil Lee Nicholas J. Bryan Justin Salamon Zeyu Jin Juhan Nam DML DRL 43 32 0 09 Aug 2020
dMelodies: A Music Dataset for Disentanglement Learning Ashis Pati Siddharth Gururani Alexander Lerch CoGe DRL 63 10 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 89 21 0 28 Jul 2020
Learning Disentangled Representations with Latent Variation Predictability Xinqi Zhu Chang Xu Dacheng Tao CoGe DRL 83 27 0 25 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 148 134 0 21 Jul 2020
PRI-VAE: Principle-of-Relevant-Information Variational Autoencoders Yanjun Li Shujian Yu José C. Príncipe Xiaolin Li D. Wu DRL 65 7 0 13 Jul 2020
Generative causal explanations of black-box classifiers Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 103 73 0 24 Jun 2020
Disentangling by Subspace Diffusion David Pfau I. Higgins Aleksandar Botev S. Racanière DiffM DRL 89 37 0 23 Jun 2020
Structure by Architecture: Structured Representations without Regularization Felix Leeb Giulia Lanzillotta Yashas Annadani M. Besserve Stefan Bauer Bernhard Schölkopf OOD CML 96 8 0 14 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
Global Distance-distributions Separation for Unsupervised Person Re-identification Xin Jin Cuiling Lan Wenjun Zeng Zhibo Chen OOD 99 69 0 01 Jun 2020
Attribute-based Regularization of Latent Spaces for Variational Auto-Encoders Ashis Pati Alexander Lerch DRL 82 3 0 11 Apr 2020
Semi-Supervised StyleGAN for Disentanglement Learning Weili Nie Tero Karras Animesh Garg Shoubhik Debhath Anjul Patney Ankit B. Patel Anima Anandkumar DRL 181 73 0 06 Mar 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 287 321 0 07 Feb 2020
Disentangled Representation Learning with Wasserstein Total Correlation Yijun Xiao William Yang Wang OOD DRL 65 12 0 30 Dec 2019
Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement Aming Wu Yahong Han Linchao Zhu Yi Yang 81 4 0 20 Nov 2019
Gated Variational AutoEncoders: Incorporating Weak Supervision to Encourage Disentanglement M. Vowels Necati Cihan Camgöz Richard Bowden CoGe DRL 66 9 0 15 Nov 2019
Weakly Supervised Disentanglement with Guarantees Rui Shu Yining Chen Abhishek Kumar Stefano Ermon Ben Poole CoGe DRL 132 139 0 22 Oct 2019
Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCI Eunjin Jeon Wonjun Ko Jee Seok Yoon Heung-Il Suk OOD 63 0 0 17 Oct 2019
Stochastic Prototype Embeddings Tyler R. Scott Karl Ridgeway Michael C. Mozer BDL UQCV 61 14 0 25 Sep 2019
Theory and Evaluation Metrics for Learning Disentangled Representations Kien Do T. Tran CoGe DRL 76 96 0 26 Aug 2019
Demystifying Inter-Class Disentanglement Aviv Gabbay Yedid Hoshen DRL 65 56 0 27 Jun 2019
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset Muhammad Waleed Gondal Manuel Wüthrich Ðorðe Miladinovic Francesco Locatello M. Breidt V. Volchkov J. Akpo Olivier Bachem Bernhard Schölkopf Stefan Bauer OOD DRL 127 139 0 07 Jun 2019
On the Fairness of Disentangled Representations Francesco Locatello G. Abbati Tom Rainforth Stefan Bauer Bernhard Schölkopf Olivier Bachem FaML DRL 81 227 0 31 May 2019
Unsupervised Model Selection for Variational Disentangled Representation Learning Sunny Duan Loic Matthey Andre Saraiva Nicholas Watters Christopher P. Burgess Alexander Lerchner I. Higgins OOD DRL 105 80 0 29 May 2019
Are Disentangled Representations Helpful for Abstract Visual Reasoning? Sjoerd van Steenkiste Francesco Locatello Jürgen Schmidhuber Olivier Bachem 110 210 0 29 May 2019
A Plug-in Method for Representation Factorization in Connectionist Models Jee Seok Yoon Wonjun Ko Heung-Il Suk 71 1 0 27 May 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 107 124 0 03 May 2019
Multi-Object Representation Learning with Iterative Variational Inference Klaus Greff Raphael Lopez Kaufman Rishabh Kabra Nicholas Watters Christopher P. Burgess Daniel Zoran Loic Matthey M. Botvinick Alexander Lerchner OCL SSL 106 510 0 01 Mar 2019
Composition and decomposition of GANs Yeu-Chern Harn Zhenghao Chen V. Jojic CoGe GAN 34 0 0 23 Jan 2019
Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs Nicholas Watters Loic Matthey Christopher P. Burgess Alexander Lerchner CoGe 113 169 0 21 Jan 2019
Recent Advances in Autoencoder-Based Representation Learning Michael Tschannen Olivier Bachem Mario Lucic OOD SSL DRL 95 447 0 12 Dec 2018
Towards a Definition of Disentangled Representations I. Higgins David Amos David Pfau S. Racanière Loic Matthey Danilo Jimenez Rezende Alexander Lerchner OCL DRL 157 481 0 05 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 205 1,476 0 29 Nov 2018
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter Ðorðe Miladinovic Bernhard Schölkopf Stefan Bauer CML OOD DRL 161 163 0 31 Oct 2018
Adapted Deep Embeddings: A Synthesis of Methods for $k$ -Shot Inductive Transfer Learning Tyler R. Scott Karl Ridgeway Michael C. Mozer 111 84 0 22 May 2018