ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1808.10805
  4. Cited By
Spherical Latent Spaces for Stable Variational Autoencoders

Spherical Latent Spaces for Stable Variational Autoencoders

31 August 2018
Jiacheng Xu
Greg Durrett
    BDL
    DRL
ArXivPDFHTML

Papers citing "Spherical Latent Spaces for Stable Variational Autoencoders"

34 / 34 papers shown
Title
Spherical Tree-Sliced Wasserstein Distance
Spherical Tree-Sliced Wasserstein Distance
Hoang V. Tran
Thanh T. Chu
K. Nguyen
Trang Pham
Tam Le
T. Nguyen
OT
61
3
0
14 Mar 2025
Hyperspherical Normalization for Scalable Deep Reinforcement Learning
Hyperspherical Normalization for Scalable Deep Reinforcement Learning
Hojoon Lee
Youngdo Lee
Takuma Seno
Donghu Kim
Peter Stone
Jaegul Choo
63
1
0
24 Feb 2025
A Coding-Theoretic Analysis of Hyperspherical Prototypical Learning Geometry
A Coding-Theoretic Analysis of Hyperspherical Prototypical Learning Geometry
Martin Lindström
Borja Rodríguez Gálvez
Ragnar Thobaben
Mikael Skoglund
40
0
0
10 Jul 2024
IMEX-Reg: Implicit-Explicit Regularization in the Function Space for
  Continual Learning
IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual Learning
Prashant Shivaram Bhat
Bharath Renjith
Elahe Arani
Bahram Zonooz
CLL
48
2
0
28 Apr 2024
AI-Generated Content (AIGC) for Various Data Modalities: A Survey
AI-Generated Content (AIGC) for Various Data Modalities: A Survey
Lin Geng Foo
Hossein Rahmani
Xiaozhong Liu
78
31
0
27 Aug 2023
VNE: An Effective Method for Improving Deep Representation by
  Manipulating Eigenvalue Distribution
VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution
Jaeill Kim
Suhyun Kang
Duhun Hwang
Jungwook Shin
Wonjong Rhee
DRL
13
21
0
04 Apr 2023
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in
  Transformer-Based Variational AutoEncoder for Diverse Text Generation
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation
Jinyi Hu
Xiaoyuan Yi
Wenhao Li
Maosong Sun
Xingxu Xie
DRL
27
0
0
22 Oct 2022
Hyperbolic VAE via Latent Gaussian Distributions
Hyperbolic VAE via Latent Gaussian Distributions
Seunghyuk Cho
Juyong Lee
Dongwoo Kim
DRL
52
5
0
30 Sep 2022
Self-supervised learning with rotation-invariant kernels
Self-supervised learning with rotation-invariant kernels
Léon Zheng
Gilles Puy
E. Riccietti
Patrick Pérez
Rémi Gribonval
SSL
19
2
0
28 Jul 2022
Spherical Sliced-Wasserstein
Spherical Sliced-Wasserstein
Clément Bonet
P. Berg
Nicolas Courty
Françcois Septier
Lucas Drumetz
Minh Pham
30
27
0
17 Jun 2022
Hyperspherical Consistency Regularization
Hyperspherical Consistency Regularization
Cheng Tan
Zhangyang Gao
Lirong Wu
Siyuan Li
Stan Z. Li
36
25
0
02 Jun 2022
Generating Multivariate Load States Using a Conditional Variational
  Autoencoder
Generating Multivariate Load States Using a Conditional Variational Autoencoder
Chenguang Wang
Ensieh Sharifnia
Zhi Gao
Simon Tindemans
Peter Palensky
29
22
0
21 Oct 2021
G-VAE, a Geometric Convolutional VAE for ProteinStructure Generation
G-VAE, a Geometric Convolutional VAE for ProteinStructure Generation
Hao Huang
Boulbaba Ben Amor
Xichan Lin
Fan Zhu
Yi Fang
DRL
26
7
0
22 Jun 2021
Discrete Auto-regressive Variational Attention Models for Text Modeling
Discrete Auto-regressive Variational Attention Models for Text Modeling
Xianghong Fang
Haoli Bai
Jian Li
Zenglin Xu
Michael Lyu
Irwin King
40
3
0
16 Jun 2021
Pseudo-Riemannian Graph Convolutional Networks
Pseudo-Riemannian Graph Convolutional Networks
Bo Xiong
Shichao Zhu
Nico Potyka
Shirui Pan
Chuan Zhou
Steffen Staab
GNN
38
28
0
06 Jun 2021
Autoencoding Under Normalization Constraints
Autoencoding Under Normalization Constraints
Sangwoong Yoon
Yung-Kyun Noh
Frank C. Park
OODD
UQCV
27
38
0
12 May 2021
Principled Interpolation in Normalizing Flows
Principled Interpolation in Normalizing Flows
Samuel G. Fadel
Sebastian Mair
Ricardo da S. Torres
Ulf Brefeld
83
3
0
22 Oct 2020
Generative Model without Prior Distribution Matching
Generative Model without Prior Distribution Matching
Cong Geng
Jia Wang
L. Chen
Zhiyong Gao
GAN
147
1
0
23 Sep 2020
Learning Sparse Prototypes for Text Generation
Learning Sparse Prototypes for Text Generation
Junxian He
Taylor Berg-Kirkpatrick
Graham Neubig
27
23
0
29 Jun 2020
Geodesics in fibered latent spaces: A geometric approach to learning
  correspondences between conditions
Geodesics in fibered latent spaces: A geometric approach to learning correspondences between conditions
Tariq Daouda
Reda Chhaibi
Prudencio Tossou
A. Villani
14
2
0
16 May 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away
A Batch Normalized Inference Network Keeps the KL Vanishing Away
Qile Zhu
Jianlin Su
Wei Bi
Xiaojiang Liu
Xiyao Ma
Xiaolin Li
D. Wu
BDL
DRL
34
61
0
27 Apr 2020
Amortised Learning by Wake-Sleep
Amortised Learning by Wake-Sleep
W. Li
Theodore H. Moskovitz
Heishiro Kanagawa
M. Sahani
OOD
23
7
0
22 Feb 2020
Variational Autoencoders with Riemannian Brownian Motion Priors
Variational Autoencoders with Riemannian Brownian Motion Priors
Dimitris Kalatzis
David Eklund
Georgios Arvanitidis
Søren Hauberg
BDL
DRL
60
48
0
12 Feb 2020
Paraphrase Generation with Latent Bag of Words
Paraphrase Generation with Latent Bag of Words
Yao Fu
Yansong Feng
John P. Cunningham
BDL
25
91
0
07 Jan 2020
Learning Representations by Maximizing Mutual Information in Variational
  Autoencoders
Learning Representations by Maximizing Mutual Information in Variational Autoencoders
Ali Lotfi-Rezaabad
S. Vishwanath
DRL
SSL
14
39
0
21 Dec 2019
Mixed-curvature Variational Autoencoders
Mixed-curvature Variational Autoencoders
Ondrej Skopek
O. Ganea
Gary Bécigneul
CML
DRL
BDL
30
101
0
19 Nov 2019
Constant Curvature Graph Convolutional Networks
Constant Curvature Graph Convolutional Networks
Gregor Bachmann
Gary Bécigneul
O. Ganea
GNN
27
132
0
12 Nov 2019
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
Bohan Li
Junxian He
Graham Neubig
Taylor Berg-Kirkpatrick
Yiming Yang
DRL
11
70
0
02 Sep 2019
Improve variational autoEncoder with auxiliary softmax multiclassifier
Improve variational autoEncoder with auxiliary softmax multiclassifier
Yao Li
DRL
23
0
0
17 Aug 2019
Effective Estimation of Deep Generative Language Models
Effective Estimation of Deep Generative Language Models
Tom Pelsmaeker
Wilker Aziz
BDL
24
27
0
17 Apr 2019
A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence
  Representations
A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence Representations
Mingda Chen
Qingming Tang
Sam Wiseman
Kevin Gimpel
DRL
23
76
0
02 Apr 2019
Lagging Inference Networks and Posterior Collapse in Variational
  Autoencoders
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
Junxian He
Daniel M. Spokoyny
Graham Neubig
Taylor Berg-Kirkpatrick
BDL
DRL
14
272
0
16 Jan 2019
A Retrieve-and-Edit Framework for Predicting Structured Outputs
A Retrieve-and-Edit Framework for Predicting Structured Outputs
Tatsunori B. Hashimoto
Kelvin Guu
Yonatan Oren
Percy Liang
BDL
KELM
36
174
0
04 Dec 2018
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
251
2,550
0
25 Jan 2016
1