Variational Inference of Disentangled Latent Concepts from Unlabeled Observations

2 November 2017

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

32 / 132 papers shown

Title
PCAAE: Principal Component Analysis Autoencoder for organising the latent space of generative networks Chi-Hieu Pham Saïd Ladjal A. Newson DRL 38 31 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 43 46 0 09 Jun 2020
Deep Learning and Knowledge-Based Methods for Computer Aided Molecular Design -- Toward a Unified Approach: State-of-the-Art and Future Directions Abdulelah S. Alshehri R. Gani Fengqi You AI4CE 32 83 0 18 May 2020
Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder Xiaojie Guo Yuanqi Du Sivani Tadepalli Liang Zhao Amarda Shehu DRL 30 26 0 08 Apr 2020
Guided Variational Autoencoder for Disentanglement Learning Zheng Ding Yifan Xu Weijian Xu Gaurav Parmar Yang Yang Max Welling Zhuowen Tu DRL CoGe 34 106 0 02 Apr 2020
Semi-Supervised StyleGAN for Disentanglement Learning Weili Nie Tero Karras Animesh Garg Shoubhik Debhath Anjul Patney Ankit B. Patel Anima Anandkumar DRL 89 72 0 06 Mar 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 26 21 0 26 Feb 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 184 313 0 07 Feb 2020
Fully-hierarchical fine-grained prosody modeling for interpretable speech synthesis Guangzhi Sun Yu Zhang Ron J. Weiss Yuanbin Cao Heiga Zen Yonghui Wu 16 130 0 06 Feb 2020
Weakly Supervised Disentanglement with Guarantees Rui Shu Yining Chen Abhishek Kumar Stefano Ermon Ben Poole CoGe DRL 56 136 0 22 Oct 2019
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs Shuyu Lin Stephen J. Roberts Niki Trigoni R. Clark DRL 21 15 0 09 Sep 2019
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations Jan Stühmer Richard Turner Sebastian Nowozin DRL BDL CoGe 117 25 0 05 Sep 2019
Theory and Evaluation Metrics for Learning Disentangled Representations Kien Do T. Tran CoGe DRL 21 93 0 26 Aug 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 29 380 0 03 Jul 2019
Tuning-Free Disentanglement via Projection Yue Bai L. Duan 21 3 0 27 Jun 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 22 46 0 19 Jun 2019
Explicit Disentanglement of Appearance and Perspective in Generative Models N. Detlefsen Søren Hauberg CoGe DRL 27 47 0 11 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 33 134 0 07 Jun 2019
Leveraging Latent Features for Local Explanations Ronny Luss Pin-Yu Chen Amit Dhurandhar P. Sattigeri Yunfeng Zhang Karthikeyan Shanmugam Chun-Chen Tu FAtt 49 37 0 29 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 11 78 0 29 May 2019
Overlearning Reveals Sensitive Attributes Congzheng Song Vitaly Shmatikov 19 148 0 28 May 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 34 123 0 03 May 2019
Relevance Factor VAE: Learning and Identifying Disentangled Factors Minyoung Kim Yuting Wang Pritish Sahu Vladimir Pavlovic CoGe CML DRL 24 39 0 05 Feb 2019
Disentangling and Learning Robust Representations with Natural Clustering Javier Antorán A. Miguel CoGe OOD CML DRL 24 19 0 27 Jan 2019
Deep Generative Learning via Variational Gradient Flow Yuan Gao Yuling Jiao Yang Wang Yao Wang Can Yang Shunkang Zhang 27 36 0 24 Jan 2019
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter Ðorðe Miladinovic Bernhard Schölkopf Stefan Bauer CML OOD DRL 19 159 0 31 Oct 2018
Hyperprior Induced Unsupervised Disentanglement of Latent Representations Abdul Fatir Ansari Harold Soh CoGe CML UD DRL 26 31 0 12 Sep 2018
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies Alessandro Achille Tom Eccles Loic Matthey Christopher P. Burgess Nicholas Watters Alexander Lerchner I. Higgins BDL 29 119 0 20 Aug 2018
Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry X. Xing Ruiqi Gao Tian Han Song-Chun Zhu Ying Nian Wu DRL 24 28 0 16 Jun 2018
Unsupervised Disentangled Representation Learning with Analogical Relations Ziyue Li Yongchuan Tang Yongxing He GAN 25 14 0 25 Apr 2018
Structured Disentangled Representations Babak Esmaeili Hao Wu Sarthak Jain Alican Bozkurt N. Siddharth Brooks Paige Dana H. Brooks Jennifer Dy Jan-Willem van de Meent OOD CML BDL DRL 36 165 0 06 Apr 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 12 1,327 0 16 Feb 2018