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Continuous Hierarchical Representations with Poincaré Variational
  Auto-Encoders

Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders

17 January 2019
Emile Mathieu
Charline Le Lan
Chris J. Maddison
Ryota Tomioka
Yee Whye Teh
    BDL
    DRL
ArXivPDFHTML

Papers citing "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders"

39 / 39 papers shown
Title
Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
Thibault de Surrel
Fabien Lotte
Sylvain Chevallier
Florian Yger
60
0
0
03 Feb 2025
A group-theoretic framework for machine learning in hyperbolic spaces
A group-theoretic framework for machine learning in hyperbolic spaces
Vladimir Jaćimović
44
0
0
12 Jan 2025
On Probabilistic Pullback Metrics for Latent Hyperbolic Manifolds
On Probabilistic Pullback Metrics for Latent Hyperbolic Manifolds
Luis Augenstein
Noémie Jaquier
Tamim Asfour
Leonel Rozo
26
0
0
28 Oct 2024
Manifold Integrated Gradients: Riemannian Geometry for Feature
  Attribution
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution
Eslam Zaher
Maciej Trzaskowski
Quan Nguyen
Fred Roosta
AAML
29
4
0
16 May 2024
Hyp-OC: Hyperbolic One Class Classification for Face Anti-Spoofing
Hyp-OC: Hyperbolic One Class Classification for Face Anti-Spoofing
Kartik Narayan
Vishal M. Patel
CVBM
41
1
0
22 Apr 2024
HyperVQ: MLR-based Vector Quantization in Hyperbolic Space
HyperVQ: MLR-based Vector Quantization in Hyperbolic Space
Nabarun Goswami
Yusuke Mukuta
Tatsuya Harada
40
4
0
18 Mar 2024
L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space
L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space
Kaushik Roy
Peyman Moghadam
Mehrtash Harandi
30
6
0
31 Jul 2023
Hyperbolic Geometry in Computer Vision: A Survey
Hyperbolic Geometry in Computer Vision: A Survey
Pengfei Fang
Mehrtash Harandi
Trung Le
Dinh Q. Phung
22
4
0
21 Apr 2023
Fully Hyperbolic Convolutional Neural Networks for Computer Vision
Fully Hyperbolic Convolutional Neural Networks for Computer Vision
Ahmad Bdeir
Kristian Schwethelm
Niels Landwehr
41
10
0
28 Mar 2023
Variational Inference for Longitudinal Data Using Normalizing Flows
Variational Inference for Longitudinal Data Using Normalizing Flows
Clément Chadebec
S. Allassonnière
BDL
DRL
26
1
0
24 Mar 2023
Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces
Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces
Li Sun
Junda Ye
Hao Peng
Feiyang Wang
Philip S. Yu
CLL
19
31
0
30 Nov 2022
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections
Clément Bonet
Laetitia Chapel
Lucas Drumetz
Nicolas Courty
16
14
0
18 Nov 2022
Hyperbolic Deep Reinforcement Learning
Hyperbolic Deep Reinforcement Learning
Edoardo Cetin
B. Chamberlain
Michael M. Bronstein
Jonathan J. Hunt
43
21
0
04 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
A Geometric Perspective on Variational Autoencoders
A Geometric Perspective on Variational Autoencoders
Clément Chadebec
S. Allassonnière
DRL
32
21
0
15 Sep 2022
Prototype Based Classification from Hierarchy to Fairness
Prototype Based Classification from Hierarchy to Fairness
Mycal Tucker
J. Shah
FaML
19
6
0
27 May 2022
Poincaré Heterogeneous Graph Neural Networks for Sequential
  Recommendation
Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation
Naicheng Guo
Xiaolei Liu
Shaoshuai Li
Qiongxu Ma
Kaixin Gao
Bing Han
Lin Zheng
Xiaobo Guo
29
14
0
16 May 2022
Visualizing Riemannian data with Rie-SNE
Visualizing Riemannian data with Rie-SNE
A. Bergsson
Søren Hauberg
35
4
0
17 Mar 2022
Provably Accurate and Scalable Linear Classifiers in Hyperbolic Spaces
Provably Accurate and Scalable Linear Classifiers in Hyperbolic Spaces
Chao Pan
Eli Chien
Puoya Tabaghi
Jianhao Peng
O. Milenkovic
18
3
0
07 Mar 2022
Riemannian statistics meets random matrix theory: towards learning from
  high-dimensional covariance matrices
Riemannian statistics meets random matrix theory: towards learning from high-dimensional covariance matrices
Salem Said
Simon Heuveline
Cyrus Mostajeran
9
8
0
01 Mar 2022
A Self-supervised Mixed-curvature Graph Neural Network
A Self-supervised Mixed-curvature Graph Neural Network
Li Sun
Zhongbao Zhang
Junda Ye
Hao Peng
Jiawei Zhang
Sen Su
Philip S. Yu
SSL
33
33
0
10 Dec 2021
Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN
  Design
Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN Design
Xiran Fan
Chun-Hao Yang
B. Vemuri
37
18
0
03 Dec 2021
Neural Distance Embeddings for Biological Sequences
Neural Distance Embeddings for Biological Sequences
Gabriele Corso
Rex Ying
Michal Pándy
Petar Velivcković
J. Leskovec
Pietro Lió
25
40
0
20 Sep 2021
Highly Scalable and Provably Accurate Classification in Poincare Balls
Highly Scalable and Provably Accurate Classification in Poincare Balls
Eli Chien
Chao Pan
Puoya Tabaghi
O. Milenkovic
30
12
0
08 Sep 2021
Clipped Hyperbolic Classifiers Are Super-Hyperbolic Classifiers
Clipped Hyperbolic Classifiers Are Super-Hyperbolic Classifiers
Yunhui Guo
Xudong Wang
Yubei Chen
Stella X. Yu
26
45
0
23 Jul 2021
On Incorporating Inductive Biases into VAEs
On Incorporating Inductive Biases into VAEs
Ning Miao
Emile Mathieu
N. Siddharth
Yee Whye Teh
Tom Rainforth
CML
DRL
27
10
0
25 Jun 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a
  Geometry-Based Variational Autoencoder
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder
Clément Chadebec
Elina Thibeau-Sutre
Ninon Burgos
S. Allassonnière
36
62
0
30 Apr 2021
Continuous normalizing flows on manifolds
Continuous normalizing flows on manifolds
Luca Falorsi
BDL
AI4CE
30
10
0
14 Mar 2021
Objective-Based Hierarchical Clustering of Deep Embedding Vectors
Objective-Based Hierarchical Clustering of Deep Embedding Vectors
Stanislav A. Naumov
G. Yaroslavtsev
Dmitrii Avdiukhin
20
23
0
15 Dec 2020
Capturing implicit hierarchical structure in 3D biomedical images with
  self-supervised hyperbolic representations
Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representations
Joy Hsu
Jeffrey Gu
Gong-Her Wu
Wah Chiu
Serena Yeung
SSL
36
27
0
03 Dec 2020
Geometrically Enriched Latent Spaces
Geometrically Enriched Latent Spaces
Georgios Arvanitidis
Søren Hauberg
Bernhard Schölkopf
DRL
19
51
0
02 Aug 2020
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action
  Recognition
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition
Wei Peng
Jingang Shi
Zhaoqiang Xia
Guoying Zhao
GNN
26
60
0
30 Jul 2020
Riemannian Continuous Normalizing Flows
Riemannian Continuous Normalizing Flows
Emile Mathieu
Maximilian Nickel
AI4CE
27
119
0
18 Jun 2020
Variational Autoencoder with Learned Latent Structure
Variational Autoencoder with Learned Latent Structure
Marissa Connor
Gregory H. Canal
Christopher Rozell
CML
DRL
18
42
0
18 Jun 2020
The Power Spherical distribution
The Power Spherical distribution
Nicola De Cao
Wilker Aziz
22
28
0
08 Jun 2020
Fine-Grain Few-Shot Vision via Domain Knowledge as Hyperspherical Priors
Fine-Grain Few-Shot Vision via Domain Knowledge as Hyperspherical Priors
B. Haney
Alexander Lavin
13
4
0
23 May 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
Constant Curvature Graph Convolutional Networks
Constant Curvature Graph Convolutional Networks
Gregor Bachmann
Gary Bécigneul
O. Ganea
GNN
27
132
0
12 Nov 2019
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