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
Leveraging Relational Information for Learning Weakly Disentangled Representations Andrea Valenti D. Bacciu CoGe DRL 35 5 0 20 May 2022
How do Variational Autoencoders Learn? Insights from Representational Similarity Lisa Bonheme M. Grzes CoGe SSL DRL 35 10 0 17 May 2022
SKILL-IL: Disentangling Skill and Knowledge in Multitask Imitation Learning Xihan Bian Oscar Alejandro Mendez Maldonado Simon Hadfield 32 6 0 06 May 2022
Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models Ali Ghadirzadeh Petra Poklukar Karol Arndt Chelsea Finn Ville Kyrki Danica Kragic Mårten Björkman OffRL 22 1 0 18 Apr 2022
StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis Zhiheng Li Martin Renqiang Min Keqin Li Chenliang Xu EGVM 38 39 0 29 Mar 2022
Attri-VAE: attribute-based interpretable representations of medical images with variational autoencoders Irem Cetin Maialen Stephens Oscar Camara M. A. G. Ballester DRL 48 39 0 20 Mar 2022
Symmetry-Based Representations for Artificial and Biological General Intelligence I. Higgins S. Racanière Danilo Jimenez Rezende AI4CE 31 44 0 17 Mar 2022
Disentangled Spatiotemporal Graph Generative Models Yuanqi Du Xiaojie Guo Hengning Cao Yanfang Ye Liang Zhao 31 21 0 28 Feb 2022
Interpretable Molecular Graph Generation via Monotonic Constraints Yuanqi Du Xiaojie Guo Amarda Shehu Liang Zhao 68 19 0 28 Feb 2022
Moment Matching Deep Contrastive Latent Variable Models Ethan Weinberger Nicasia Beebe-Wang Su-In Lee 31 16 0 21 Feb 2022
CITRIS: Causal Identifiability from Temporal Intervened Sequences Phillip Lippe Sara Magliacane Sindy Löwe Yuki M. Asano Taco S. Cohen E. Gavves CML 46 101 0 07 Feb 2022
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement Xiaoting Shao Karl Stelzner Kristian Kersting CML DRL 29 3 0 01 Feb 2022
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Jackson Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 39 7 0 29 Dec 2021
Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models Alon Jacovi Junyoung Lee Alexander Lerch DRL 23 1 0 20 Dec 2021
On Causally Disentangled Representations Abbavaram Gowtham Reddy Benin Godfrey L V. Balasubramanian OOD CML 34 21 0 10 Dec 2021
3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces Simone Foti Bongjin Koo Danail Stoyanov Matthew J. Clarkson CoGe 19 15 0 24 Nov 2021
Illiterate DALL-E Learns to Compose Gautam Singh Fei Deng Sungjin Ahn CoGe OCL 27 133 0 17 Oct 2021
Discovery of Single Independent Latent Variable Uri Shaham Jonathan Svirsky Ori Katz Ronen Talmon CML 28 2 0 12 Oct 2021
Evaluation of Latent Space Disentanglement in the Presence of Interdependent Attributes Karn N. Watcharasupat Alexander Lerch 26 2 0 11 Oct 2021
On the relationship between disentanglement and multi-task learning Lukasz Maziarka A. Nowak Maciej Wołczyk Andrzej Bedychaj OOD DRL 27 3 0 07 Oct 2021
Be More Active! Understanding the Differences between Mean and Sampled Representations of Variational Autoencoders Lisa Bonheme M. Grzes DRL 19 6 0 26 Sep 2021
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models Maciej Wołczyk Magdalena Proszewska Lukasz Maziarka Maciej Ziȩba Patryk Wielopolski Rafał Kurczab Marek Śmieja DRL 29 5 0 18 Sep 2021
Let the CAT out of the bag: Contrastive Attributed explanations for Text Saneem A. Chemmengath A. Azad Ronny Luss Amit Dhurandhar FAtt 34 10 0 16 Sep 2021
From Heatmaps to Structural Explanations of Image Classifiers Li Fuxin Zhongang Qi Saeed Khorram Vivswan Shitole Prasad Tadepalli Minsuk Kahng Alan Fern XAI FAtt 23 4 0 13 Sep 2021
Desiderata for Representation Learning: A Causal Perspective Yixin Wang Michael I. Jordan CML 32 82 0 08 Sep 2021
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation Yuxiang Wei Yupeng Shi Xiao-Chang Liu Zhilong Ji Yuan Gao Zhongqin Wu W. Zuo 28 55 0 17 Aug 2021
Is Disentanglement enough? On Latent Representations for Controllable Music Generation Ashis Pati Alexander Lerch CoGe DRL 25 16 0 01 Aug 2021
On Incorporating Inductive Biases into VAEs Ning Miao Emile Mathieu N. Siddharth Yee Whye Teh Tom Rainforth CML DRL 30 10 0 25 Jun 2021
Commutative Lie Group VAE for Disentanglement Learning Xinqi Zhu Chang Xu Dacheng Tao CoGe DRL 40 22 0 07 Jun 2021
Exploring Autoencoder-based Error-bounded Compression for Scientific Data Jinyang Liu Sheng Di Kai Zhao Sian Jin Dingwen Tao Xin Liang Zizhong Chen Franck Cappello 19 49 0 25 May 2021
Discover the Unknown Biased Attribute of an Image Classifier Zhiheng Li Chenliang Xu 30 50 0 29 Apr 2021
Where and What? Examining Interpretable Disentangled Representations Xinqi Zhu Chang Xu Dacheng Tao FAtt DRL 56 38 0 07 Apr 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 41 297 0 03 Mar 2021
Learning disentangled representations via product manifold projection Marco Fumero Luca Cosmo Simone Melzi Emanuele Rodolà CoGe DRL 23 22 0 02 Mar 2021
Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View Xuanchi Ren Tao Yang Yuwang Wang W. Zeng CoGe OCL DRL 38 37 0 21 Feb 2021
Towards Building A Group-based Unsupervised Representation Disentanglement Framework Tao Yang Xuanchi Ren Yuwang Wang W. Zeng Nanning Zheng CoGe DRL 24 27 0 20 Feb 2021
Measuring Disentanglement: A Review of Metrics M. Carbonneau Julian Zaïdi Jonathan Boilard G. Gagnon CoGe DRL 28 81 0 16 Dec 2020
Multi-type Disentanglement without Adversarial Training Lei Sha Thomas Lukasiewicz DRL 49 12 0 16 Dec 2020
On the Transfer of Disentangled Representations in Realistic Settings Andrea Dittadi Frederik Trauble Francesco Locatello M. Wuthrich Vaibhav Agrawal Ole Winther Stefan Bauer Bernhard Schölkopf OOD 35 80 0 27 Oct 2020
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 11 66 0 27 Oct 2020
Deep Anomaly Detection by Residual Adaptation Lucas Deecke Lukas Ruff Robert A. Vandermeulen Hakan Bilen UQCV 30 4 0 05 Oct 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 32 18 0 27 Aug 2020
Linear Disentangled Representations and Unsupervised Action Estimation Matthew Painter Jonathon S. Hare Adam Prugel-Bennett CoGe DRL 39 20 0 18 Aug 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 29 20 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 44 9 0 26 Jul 2020
Learning Disentangled Representations with Latent Variation Predictability Xinqi Zhu Chang Xu Dacheng Tao CoGe DRL 22 26 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 48 132 0 21 Jul 2020
Learning latent representations across multiple data domains using Lifelong VAEGAN Fei Ye A. Bors SyDa CLL 12 65 0 20 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 16 47 0 16 Jul 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 29 115 0 14 Jun 2020