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CausalVAE: Structured Causal Disentanglement in Variational Autoencoder

CausalVAE: Structured Causal Disentanglement in Variational Autoencoder

18 April 2020
Mengyue Yang
Furui Liu
Zhitang Chen
Xinwei Shen
Jianye Hao
Jun Wang
    OOD
    CoGe
    CML
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Papers citing "CausalVAE: Structured Causal Disentanglement in Variational Autoencoder"

12 / 12 papers shown
Title
Conditionally Invariant Representation Learning for Disentangling
  Cellular Heterogeneity
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity
H. Aliee
Ferdinand Kapl
Soroor Hediyeh-zadeh
Fabian J. Theis
CML
20
6
0
02 Jul 2023
Deep Causal Learning for Robotic Intelligence
Deep Causal Learning for Robotic Intelligence
Y. Li
CML
32
5
0
23 Dec 2022
De-Biasing Generative Models using Counterfactual Methods
De-Biasing Generative Models using Counterfactual Methods
Sunay Bhat
Jeffrey Q. Jiang
Omead Brandon Pooladzandi
Gregory Pottie
CML
28
7
0
04 Jul 2022
A Causal Lens for Controllable Text Generation
A Causal Lens for Controllable Text Generation
Zhiting Hu
Erran L. Li
42
59
0
22 Jan 2022
On Causally Disentangled Representations
On Causally Disentangled Representations
Abbavaram Gowtham Reddy
Benin Godfrey L
V. Balasubramanian
OOD
CML
28
21
0
10 Dec 2021
Matching Learned Causal Effects of Neural Networks with Domain Priors
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti
Abbavaram Gowtham Reddy
V. Balasubramanian
Amit Sharma
CML
28
12
0
24 Nov 2021
LDC-VAE: A Latent Distribution Consistency Approach to Variational
  AutoEncoders
LDC-VAE: A Latent Distribution Consistency Approach to Variational AutoEncoders
Xiaoyu Chen
Chen Gong
Qiang He
Xinwen Hou
Yu Liu
25
1
0
22 Sep 2021
Learning Causal Semantic Representation for Out-of-Distribution
  Prediction
Learning Causal Semantic Representation for Out-of-Distribution Prediction
Chang-Shu Liu
Xinwei Sun
Jindong Wang
Haoyue Tang
Tao Li
Tao Qin
Wei Chen
Tie-Yan Liu
CML
OODD
OOD
24
104
0
03 Nov 2020
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse
  Coding
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
34
132
0
21 Jul 2020
On Disentangled Representations Learned From Correlated Data
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
26
115
0
14 Jun 2020
Deep Structural Causal Models for Tractable Counterfactual Inference
Deep Structural Causal Models for Tractable Counterfactual Inference
Nick Pawlowski
Daniel Coelho De Castro
Ben Glocker
CML
MedIm
27
229
0
11 Jun 2020
Masked Gradient-Based Causal Structure Learning
Masked Gradient-Based Causal Structure Learning
Ignavier Ng
Shengyu Zhu
Zhuangyan Fang
Haoyang Li
Zhitang Chen
Jun Wang
CML
83
117
0
18 Oct 2019
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