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Progressive Learning and Disentanglement of Hierarchical Representations

Progressive Learning and Disentanglement of Hierarchical Representations

24 February 2020
Zhiyuan Li
J. Murkute
P. Gyawali
Linwei Wang
    DRL
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Papers citing "Progressive Learning and Disentanglement of Hierarchical Representations"

13 / 13 papers shown
Title
Graph-based Unsupervised Disentangled Representation Learning via
  Multimodal Large Language Models
Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models
Baao Xie
Qiuyu Chen
Yunnan Wang
Zequn Zhang
Xin Jin
Wenjun Zeng
OffRL
50
2
0
26 Jul 2024
A Category-theoretical Meta-analysis of Definitions of Disentanglement
A Category-theoretical Meta-analysis of Definitions of Disentanglement
Yivan Zhang
Masashi Sugiyama
43
3
0
11 May 2023
Disentangled Representation Learning
Disentangled Representation Learning
Xin Eric Wang
Hong Chen
Siao Tang
Zihao Wu
Wenwu Zhu
DRL
45
79
0
21 Nov 2022
Disentanglement of Correlated Factors via Hausdorff Factorized Support
Disentanglement of Correlated Factors via Hausdorff Factorized Support
Karsten Roth
Mark Ibrahim
Zeynep Akata
Pascal Vincent
Diane Bouchacourt
CML
OOD
CoGe
41
33
0
13 Oct 2022
Interaction Modeling with Multiplex Attention
Interaction Modeling with Multiplex Attention
Fan-Yun Sun
Isaac Kauvar
Ruohan Zhang
Jiachen Li
Mykel Kochenderfer
Jiajun Wu
Nick Haber
29
19
0
23 Aug 2022
Towards Unsupervised Content Disentanglement in Sentence Representations
  via Syntactic Roles
Towards Unsupervised Content Disentanglement in Sentence Representations via Syntactic Roles
G. Felhi
Joseph Le Roux
Djamé Seddah
DRL
23
5
0
22 Jun 2022
Exploiting Inductive Bias in Transformers for Unsupervised
  Disentanglement of Syntax and Semantics with VAEs
Exploiting Inductive Bias in Transformers for Unsupervised Disentanglement of Syntax and Semantics with VAEs
G. Felhi
Joseph Le Roux
Djamé Seddah
DRL
32
2
0
12 May 2022
ProgFed: Effective, Communication, and Computation Efficient Federated
  Learning by Progressive Training
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
Hui-Po Wang
Sebastian U. Stich
Yang He
Mario Fritz
FedML
AI4CE
36
48
0
11 Oct 2021
Task-Generic Hierarchical Human Motion Prior using VAEs
Task-Generic Hierarchical Human Motion Prior using VAEs
Jiaman Li
Ruben Villegas
Duygu Ceylan
Jimei Yang
Zhengfei Kuang
Hao Li
Yajie Zhao
3DH
30
45
0
07 Jun 2021
Commutative Lie Group VAE for Disentanglement Learning
Commutative Lie Group VAE for Disentanglement Learning
Xinqi Zhu
Chang Xu
Dacheng Tao
CoGe
DRL
45
22
0
07 Jun 2021
Where and What? Examining Interpretable Disentangled Representations
Where and What? Examining Interpretable Disentangled Representations
Xinqi Zhu
Chang Xu
Dacheng Tao
FAtt
DRL
61
38
0
07 Apr 2021
Measuring Disentanglement: A Review of Metrics
Measuring Disentanglement: A Review of Metrics
M. Carbonneau
Julian Zaïdi
Jonathan Boilard
G. Gagnon
CoGe
DRL
33
82
0
16 Dec 2020
Controlling the Interaction Between Generation and Inference in
  Semi-Supervised Variational Autoencoders Using Importance Weighting
Controlling the Interaction Between Generation and Inference in Semi-Supervised Variational Autoencoders Using Importance Weighting
G. Felhi
Joseph Leroux
Djamé Seddah
BDL
31
1
0
13 Oct 2020
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