Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
Recently, hyperbolic spaces have emerged as a promising alternative for processing data with a tree-like structure or power-law distribution, owing to its exponential growth property and tree-likeness prior. Different from the Euclidean space, which expands polynomially, the hyperbolic space grows exponentially which makes it gain natural advantages in abstracting tree-like or scale-free data with hierarchical organizations. In this repository, we categorize papers related to hyperbolic representation learning into different types to facilitate researcher studies and to promote the development of the community. We will keep updating this repository with the latest research developments. We are aware that there will inevitably be some mistakes and oversights, so if you have any questions or suggestions, please feel free to contact us ([email protected]).
Hyperbolic Slack Group
Fully Hyperbolic Convolutional Neural Networks for Computer Vision, ICLR 2024
The Dark Side of the Hyperbolic Moon, ICLR 2024
Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design, ICLR 2024
Fast Hyperboloid Decision Tree Algorithms, ICLR 2024
Matrix Manifold Neural Networks++, ICLR 2024
Hyperbolic VAE via Latent Gaussian Distributions, NeurIPS 2023
Seunghyuk Cho, Juyong Lee, Dongwoo Kim
Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels, NeurIPS, 2023
Shu-Lin Xu, Yifan Sun, Faen Zhang, Anqi Xu, Xiu-Shen Wei, Yi Yang
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach, NeurIPS 2023
Nurendra Choudhary, Nikhil Rao, Chandan K. Reddy
Fitting trees to $\ell_1$-hyperbolic distances, NeurIPS 2023
Joon-Hyeok Yim, Anna Gilbert
Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design, arxiv 2023
Heng Dong, Junyu Zhang, Chongjie Zhang
Alignment and Outer Shell Isotropy for Hyperbolic Graph Contrastive Learning, arxiv 2023
Yifei Zhang, Hao Zhu, Jiahong Liu, Piotr Koniusz, Irwin King
Riemannian Residual Neural Networks, arxiv 2023
Isay Katsman, Eric Ming Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser-Nam Lim, Christopher De Sa
Tempered Calculus for ML: Application to Hyperbolic Model Embedding, arxiv 2024
Richard Nock, Ehsan Amid, Frank Nielsen, Alexander Soen, Manfred K. Warmuth
Hyperbolic Deep Learning in Computer Vision: A Survey, arxiv 2023
Pascal Mettes, Mina Ghadimi Atigh, Martin Keller-Ressel, Jeffrey Gu, Serena Yeung
Hyperbolic Graph Neural Networks: A Review of Methods and Application, arxiv 2022.
GitHub
Menglin Yang, Min Zhou, Zhihao Li, Jiahong Liu, Lujia Pan, Hui Xiong, Irwin King
Hyperbolic Deep Neural Networks: A Survey, TPAMI 2022.
GitHub
Wei Peng, Tuomas Varanka, Abdelrahman Mostafa, Henglin Shi, Guoying Zhao
Hyperbolic Geometry in Computer Vision: A Survey, arxiv 2023.
Pengfei Fang, Mehrtash Harandi, Trung Le, Dinh Phung
An Introduction to Geometric Topology, 2022
Bruno Martelli
Hyperbolic Geometry, 2020.
Brice Loustau
Manifolds and Differential Geometry, 2009.
Jeffrey M. Lee
Introduction to Hyperbolic Geometry, 1995.
A Ramsay, RD Richtmyer
Geoopt: Riemannian Adaptive Optimization Methods ICLR 2019
Max Kochurov and Rasul Karimov and Serge Kozlukov
Curvature Learning Framework
Alibaba
GraphZoo: A Development Toolkit for Graph Neural Networks with Hyperbolic Geometries WWW 2022
Anoushka Vyas, Nurendra Choudhary, Mehrdad Khatir, Chandan K. Reddy
HypLL: The Hyperbolic Learning Library, GitHub
Max van Spengler, Philipp Wirth, Pascal Mettes
Hyperbolic Deep Learning for Computer Vision
Pascal Mettes, Max van Spengler, Yunhui Guo, Stella Yu
Hyperbolic networks: Theory, Architecture and Applications
Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan Reddy
Hyperbolic Graph Neural Networks: A Tutorial on Methods and Applications, KDD 2023
Min Zhou, Menglin Yang, Bo Xiong, Hui Xiong, Irwin King
Hyperbolic Representation Learning for Computer Vision. Tutorial 2022
Pascal Mettes, Mina Ghadimi Atigh, Martin Keller-Ressel, Jeffrey Gu, Serena Yeung@ECCV2022
https://hyperbolic-representation-learning.readthedocs.io/en/latest/
Hyperbolic Graph Representation Learning. Tutorial 2022
Min Zhou, Menglin Yang, Lujia Pan, Irwin King @ ECML-PKDD 2022
Hyperbolic Neural Network. Tutorial 2022
Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan Sengamedu, Chandan Reddy @ KDD 2022
Hyperbolic Hyperbolic embeddings in machine learning and deep learning. Tutorial 2020
Octavian Ganea 2020.
Poincaré Embeddings for Learning Hierarchical Representations, NeurIPS 2017
Maximilian Nickel, Douwe Kiela
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry, ICML 2018
Maximilian Nickel, Douwe Kiela
Representation Tradeoffs for Hyperbolic Embeddings, ICML 2018
Frederic Sala, Christopher De Sa, Albert Gu, Christopher Re´
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings, ICML 2018
Octavian-Eugen Ganea, Gary Bécigneul, Thomas Hofmann
Lorentzian Distance Learning for Hyperbolic Representations, ICML 2019
Marc T. Law, Renjie Liao, Jake Snell, Richard S. Zemel
Hyperbolic Disk Embeddings for Directed Acyclic Graphs, ICML 2019
Ryota Suzuki, Ryusuke Takahama, Shun Onoda
Hyperbolic Neural Networks, NeurIPS 2018
Octavian-Eugen Ganea, Gary Bécigneul, Thomas Hofmann
Hyperbolic Attention Networks, ICLR 2019
Caglar Gulcehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders, NeurIPS 2019
Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, Yee Whye Teh
Hyperbolic Neural Network++, ICLR 2021
Ryohei Shimizu, Yusuke Mukuta, Tatsuya Harada
Fully Hyperbolic Neural Networks, ACL 2022
Weize Chen, Xu Han, Yankai Lin, Hexu Zhao, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou
Poincaré ResNet, arxiv 2023
Max van Spengler, Erwin Berkhout, Pascal Mettes
Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN Design, CVPR 2022
Xiran Fan, Chun-Hao Yang, Baba C. Vemuri
Hyperbolic Graph Convolutional Neural Networks, NeurIPS 2019
Ines Chami*, Rex Ying*, Christopher Ré, Jure Leskovec
Hyperbolic Graph Neural Network, NeurIPS 2019
Qi Liu, Maximilian Nickel, Douwe Kiela
Lorentzian Graph Convolutional Networks, WWW 2021
Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song
A Hyperbolic-to-Hyperbolic Graph Convolutional Network, CVPR 2021
Jindou Dai, Yuwei Wu, Zhi Gao, Yunde Jia
Hyperbolic Graph Attention Network, Transcations on Big Data 2021
Yiding Zhang, Xiao Wang, Xunqiang Jiang, Chuan Shi, Yanfang Ye
Unsupervised Hyperbolic Representation Learning via Message Passing Auto-Encoders, CVPR 2021
Jiwoong Park, Junho Cho, Hyung Jin Chang, Jin Young Choi
$\kappa$HGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning, KDD 2023
Menglin Yang, Min Zhou, Lujia Pan, Irwin King
Residual Hyperbolic Graph Convolution Networks, AAAI 2024
Yangkai Xue, Jindou Dai, Zhipeng Lu, Yuwei Wu, Yunde Jia
Representation Tradeoffs for Hyperbolic Embeddings, ICML 2018
Christopher De Sa, Albert Gu, Christopher Ré, Frederic Sala
Generalization Error Bound for Hyperbolic Ordinal Embedding, ICML 2021
Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Marc Cavazza, Kenji Yamanishi
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic, NeurIPS 2021
Atsushi Suzuki, Atsushi Nitanda, jing wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza
Hyperbolic vs Euclidean Embeddings in Few-Shot Learning: Two Sides of the Same Coin WACV
Gabriel Moreira, Manuel Marques, João Paulo Costeira, Alexander Hauptmann
Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender Systems KDD 2021
Sixiao Zhang, Hongxu Chen, Xiao Ming, Lizhen Cui, Hongzhi Yin, Guandong Xu
Learning mixed-curvature representations in product spaces, ICLR 2019
Albert Gu, Frederic Sala, Beliz Gunel, Christopher Ré
Mixed-curvature variational autoencoders, ICLR 2020
Skopek, Ondrej, Octavian-Eugen Ganea, and Gary Bécigneul
Constant Curvature Graph Convolutional Networks, ICML 2020
Gregor Bachmann, Gary Bécigneul, Octavian-Eugen Ganea
Mixed-curvature multi-relational graph neural network for knowledge graph completion, WWW 2021
Wang, Shen, Xiaokai Wei, Cicero Nogueira Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew Arnold, Bing Xiang, Philip S. Yu, and Isabel F. Cruz.
A Self-supervised Mixed-curvature Graph Neural Network, AAAI 2022
Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu
Enhancing Hyperbolic Graph Embeddings via Contrastive Learning, NeurIPS 2021 SSL Workshop
Jiahong Liu, Menglin Yang, Min Zhou, Shanshan Feng, Philippe Fournier-Viger
Geometry Interaction Learning, NeurIPS 2020
Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao, Bin Wang
FMGNN: Fused Manifold Graph Neural Network, TKDD 2023
Cheng Deng, Fan Xu, Jiaxing Ding, Luoyi Fu, Weinan Zhang, Xinbing Wang
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning, arxiv 2023
Sungjun Cho, Seunghyuk Cho, Sungwoo Park, Hankook Lee, Honglak Lee, Moontae Lee
Directed Graph Embeddings in Pseudo-Riemannian Manifolds, ICML 2021
Aaron Sim, Maciej Wiatrak, Angus Brayne, Páidí Creed, Saee Paliwal
Semi-Riemannian Graph Convolutional Networks, NeurIPS 2022
Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, Steffen Staab
Ultrahyperbolic Neural Networks, NeurIPS 2021
Marc T Law
Ultrahyperbolic Representation Learning, NeurIPS 2020
Marc T. Law, Jos Stam
Latent Variable Modelling with Hyperbolic Normalizing Flows, ICML 2020
Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton
Hyperbolic Graph Diffusion Model, AAAI 2024
Lingfeng Wen, Xuan Tang, Mingjie Ouyang, Xiangxiang Shen, Jian Yang, Daxin Zhu, Mingsong Chen, Xian Wei
Hyperbolic VAE via Latent Gaussian Distributions, NeurIPS 2023
Seunghyuk Cho, Juyong Lee, Dongwoo Kim
Lorentzian fully hyperbolic generative adversarial network, arxiv 2022
Eric Qu, Dongmian Zou
Mean Computation and BatchNorm
Differentiating through the Fréchet Mean, ICML 2020
Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, Christopher De Sa
Sampling
Wrapped Distributions on homogeneous Riemannian manifolds, 2022
Fernando Galaz-Garcia, Marios Papamichalis, Kathryn Turnbull, Simon Lunagomez, Edoardo Airoldi
MixUp and Data Augmentation
HYPMIX: Hyperbolic Interpolative Data Augmentation, EMNLP 2021
Ramit Sawhney, Megh Thakkar, Shivam Agarwal, Di Jin, Diyi Yang, Lucie Flek
PCA
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections, ICML 2021
Ines Chami*, Albert Gu*, Dat Nguyen, Christopher Ré
TSNE
Accelerating hyperbolic t-SNE, arxiv 2024
Martin Skrodzki, Hunter van Geffen, Nicolas F. Chaves-de-Plaza, Thomas Höllt, Elmar Eisemann, Klaus Hildebrandt
Language Models as Hierarchy Encoders, arxiv 2024
Yuan He, Zhangdie Yuan, Jiaoyan Chen, Ian Horrocks
HyperSDFusion: Bridging Hierarchical Structures in Language and Geometry for Enhanced 3D Text2Shape Generation, arxiv 2024
Zhiying Leng, Tolga Birdal, Xiaohui Liang, Federico Tombari
LLMs are Good Action Recognizers, arxiv 2024
Haoxuan Qu, Yujun Cai, Jun Liu
HICF: Hyperbolic Informative Collaborative Filtering, KDD 2022
Menglin Yang, Zhihao Li, Min Zhou, Jiahong Liu, Irwin King
HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization, WWW 2022
Menglin Yang, Min Zhou, Jiahong Liu, Defu Lian, Irwin King
HGCF: Hyperbolic Graph Convolution Networks for Collaborative Filtering, WWW 2021
Jianing Sun,Zhaoyue Cheng,Saba Zuberi,Felipe Perez,Maksims Volkovs
HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation, SIGIR 2022
Yuntao Du, Xinjun Zhu, Lu Chen, Baihua Zheng, and Yunjun Gao
Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation, WSDM 2022
Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King
Geometric Inductive Matrix Completion: A Hyperbolic Approach with Unified Message Passing, WSDM 2022
Chengkun Zhang , Hongxu Chen , Sixiao Zhang , Guandong Xu , Junbin Gao
Hypersorec: Exploiting hyperbolic user and item representations with multiple aspects for social-aware recommendation, TOIS 2021
Hao Wang, Defu Lian, Hanghang Tong, Qi Liu, Zhenya Huang and Enhong Chen
Knowledge Based Hyperbolic Propagation, SIGIR short paper 2021
Chang-You Tai, Chien-Kun Huang, Liang-Ying Huang, Lun-Wei Ku
HSR: hyperbolic social recommender, Information Sciences 2022
Anchen Li, Bo Yang
Enhancing Hierarchy-Aware Graph Networks with Deep Dual Clustering for Session-based Recommendation, WWW 2023
Jiajie Su, Chaochao Chen, Weiming Liu, Fei Wu, Xiaolin Zheng, Haoming Lyu
HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation, arxiv 2021
Naicheng Guo, Xiaolei Liu, Shaoshuai Li, Qiongxu Ma, Yunan Zhao, Bing Han, Lin Zheng, Kaixin Gao, Xiaobo Guo
Hyperbolic Hypergraphs for Sequential Recommendation, CIKM 2021
Yicong Li, Hongxu Chen, Xiangguo Sun, Zhenchao Sun, Lin Li, Lizhen Cui, Philip S. Yu, Guandong Xu
HGCC: Enhancing Hyperbolic Graph Convolution Networks on Heterogeneous Collaborative Graph for Recommendation, arxiv 2022
Lu Zhang, Ning Wu
Lorentz Equivariant Model for Knowledge-Enhanced Collaborative Filtering, arxiv 2023
Bosong Huang, Weihao Yu, Ruzhong Xie, Jing Xiao, Jin Huang
Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender Systems KDD 2021
Sixiao Zhang, Hongxu Chen, Xiao Ming, Lizhen Cui, Hongzhi Yin, Guandong Xu
HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems, WSDM 2020
Lucas Vinh Tran, Yi Tay, Shuai Zhang, Gao Cong, Xiaoli Li
Learning Feature Interactions with Lorentzian Factorization Machine, AAAI 2020
Canran Xu, Ming Wu
Scalable Hyperbolic Recommender Systems, WSDM 2020
Benjamin Paul Chamberlain, Stephen R. Hardwick, David R. Wardrope, Fabon Dzogang, Fabio Daolio, Saúl Vargas
A hyperbolic metric embedding approach for next-poi recommendation, SIGIR 2020
Shanshan Feng , Lucas Vinh Tran , Gao Cong , Lisi Chen , Jing Li , Fan Li
Node2LV: Squared Lorentzian Representations for Node Proximity, ICDE 2021
Shanshan Feng, Lisi Chen, Kaiqi Zhao, Wei Wei, Fan Li, Shuo Shang
Hyperbolic Neural Collaborative Recommender, TKDE 2022
Anchen Li; Bo Yang; Huan Huo; Hongxu Chen; Guandong Xu; Zhen Wang
Enhancing Recommendation with Automated Tag Taxonomy Construction in Hyperbolic Space, ICDE 2022
Yanchao Tan; Carl Yang; Xiangyu Wei; Chaochao Chen; Longfei Li; Xiaolin Zheng
Hyperbolic Personalized Tag Recommendation, DASFAA 2022
Weibin Zhao, Aoran Zhang, Lin Shang, Yonghong Yu, Li Zhang, Can Wang, Jiajun Chen & Hongzhi Yin
Low-Dimensional Hyperbolic Knowledge Graph Embeddings, ACL 2019
Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, Christopher Ré
Multi-relational Poincaré Graph Embeddings, NeurIPS 2019
Ivana Balažević, Carl Allen, Timothy Hospedales
Knowledge Association with Hyperbolic Knowledge Graph Embeddings, EMNLP 2020
Zequn Sun, Muhao Chen, Wei Hu, Chengming Wang, Jian Dai, Wei Zhang
Knowledge Graph Representation via Hierarchical Hyperbolic Neural Graph Embedding, IEEE Big Data
Shen Wang, Xiaokai Wei, Cicero Nogueira Dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew Arnold, Philip S. Yu
Mixed-Curvature Multi-relational Graph Neural Network for Knowledge Graph Completion, WWW 2021
Shen Wang , Xiaokai Wei , Cicero Nogueira Nogueira dos Santos , Zhiguo Wang , Ramesh Nallapati , Andrew Arnold , Bing Xiang , Philip S. Yu , Isabel F. Cruz
Geometry Interaction Knowledge Graph Embeddings for KG embedding, AAAI 2022
Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones, NeurIPS 2021
Yushi Bai, Rex Ying, Hongyu Ren, Jure Leskovec
Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures, ACL 2021
Sebastien Montella, Lina Rojas-Barahona, Johannes Heinecke
Self-supervised hyperboloid representations from logical queries over knowledge graphs, WWW 2021
Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy
HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion, arxiv
Prodromos Kolyvakis, Alexandros Kalousis, Dimitris Kiritsis
Hyperbolic Hierarchy-Aware Knowledge Graph Embedding for Link Prediction. EMNLP findings 2021
Zhe Pan, Peng Wang
FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion,arxiv 2023
Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He
Mixed Geometry Message and Trainable Convolutional Attention Network for Knowledge Graph Completion, AAAI 2024
Bin Shang, Yinliang Zhao, Jun Liu, Di Wang
Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method, Briefings in Bioinformatics 2021
Zhenxing Wu, Dejun Jiang, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Dongsheng Cao, Tingjun Hou
Semi-supervised hierarchical drug embedding inhyperbolic space, J. Chem. Inf. Model 2020
Ke Yu*, Shyam Visweswaran*, and Kayhan Batmanghelich
HiG2Vec: hierarchical representations of Gene Ontology and genes in the Poincaré ball, Bioinformatics, 2021
Jaesik Kim, Dokyoon Kim, Kyung-Ah Sohn
Contrastive Poincaré Maps for single-cell data analysis, ICLR workshop 2024
Nithya Bhasker, Hattie Chung, Louis Boucherie, Vladislav Kim, Stefanie Speidel, Melanie Weber
Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space, KDD 2021
Menglin Yang, Min Zhou, Marcus Kalander, Zengfeng Huang, Irwin King
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs, AAAI 2021
Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu
Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading, WWW 2021
Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa , Rajiv Shah
SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds, WWW 2023
Junda Ye, Zhongbao Zhang, Li Sun, Yang Yan, Feiyang Wang, Fuxin Ren
Hyperbolic Heterogeneous Information Network Embedding, AAAI 2020
Xiao Wang, Yiding Zhang, Chuan Shi
Embedding Heterogeneous Information Network in Hyperbolic Spaces, TKDD 2022
Yiding Zhang, Xiao Wang, Nian Liu, Chuan Shi
Hyperbolic Disk Embeddings for Directed Acyclic Graphs,ICML 2019
Ryota Suzuki, Ryusuke Takahama, Shun Onoda
A hyperbolic Embedding Model for Directed Networks
Zongning Wu, Zengru Di, Ying Fan (this paper includes many errors)
Hyperbolic Node Embedding for Signed Networks, Neurcomputing 2021
Wenzhuo Song, Hongxu Chen, Xueyan Liu, Hongzhe Jiang, Shengsheng Wang
HEAT: Hyperbolic Embedding of Attributed Networks, IDEAL 2020
David McDonald, Shan He
Hyperbolic Multiplex Network Embedding with Maps of Random Walk
Peiyuan Sun
Poincare Glove: Hyperbolic Word Embeddings, ICLR 2019
Alexandru Tifrea and Gary Becigneul and Octavian-Eugen Gane
Skip-gram word embeddings in hyperbolic space, ACL 2018
Matthias Leimeister, Benjamin J. Wilson
Embedding text in hyperbolic spaces, ACL 2018
Bhuwan Dhingra, Christopher J. Shallue, Mohammad Norouzi, Andrew M. Dai, George E. Dahl
Hyperbolic entailment cones for learning hierarchical embeddings, ICML 2018
Octavian-Eugen Ganea, Gary Bécigneul, Thomas Hofmann
Low-rank approximations of hyperbolic embeddings
Pratik Jawanpuria, Mayank Meghwanshi, Bamdev Mishra
Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings
Matt Le, Stephen Roller, Laetitia Papaxanthos, Douwe Kiela, Maximilian Nickel
Hyperbolic interaction model for hierarchical multi-label classification, AAAI 2021
Boli Chen, Xin Huang, Lin Xiao, Zixin Cai, Liping Jing
Hyperbolic Capsule Networks for Multi-Label Classification, ACL 2020
Boli Chen, Xin Huang, Lin Xiao, Liping Jing
Joint Learning of Hyperbolic Label Embeddings for Hierarchical Multi-label Classification, EACL 2021
Soumya Chatterjee, Ayush Maheshwari, Ganesh Ramakrishnan, Saketha Nath Jagaralpudi
Hyperbolic Embeddings for Hierarchical Multi-label Classification, 2020
Tomaž StepišnikEmail, Dragi Kocev
A Fully Hyperbolic Neural Model for Hierarchical Multi-Class Classification, EMNLP findings
Federico López, Michael Strube
Hyperbolic Relevance Matching for Neural Keyphrase Extraction for key phrases matching, Naacl 2022
Mingyang Song, Yi Feng, Liping Jing
Cross-lingual Word Embeddings in Hyperbolic Space for word embedding, arxiv 2022 Chandni Saxena, Mudit Chaudhary, Helen Meng
Improving Visual Recognition with Hyperbolical Visual Hierarchy Mapping Hyeongjun Kwon, Jinhyun Jang, Jin Kim, Kwonyoung Kim, Kwanghoon Sohn
HyperSDFusion: Bridging Hierarchical Structures in Language and Geometry for Enhanced 3D Text2Shape Generation, arxiv 2024
Zhiying Leng, Tolga Birdal, Xiaohui Liang, Federico Tombari
Hyperbolic Image Embedding, CVPR 2020
Valentin Khrulkov, Leyla Mirvakhabova, Evgeniya Ustinova, Ivan Oseledets, Victor Lempitsky
Hyperbolic Image Segmentation, CVPR 2022
Mina GhadimiAtigh, Julian Schoep, Erman Acar, Nanne van Noord, Pascal Mettes
Hyperbolic Vision Transformers: Combining Improvements in Metric Learning,CVPR 2022
Aleksandr Ermolov, Leyla Mirvakhabova, Valentin Khrulkov, Nicu Sebe, Ivan Oseledets
Hyperbolic Image-Text Representations, ICML 2023
Karan Desai, Maximilian Nickel, Tanmay Rajpurohit, Justin Johnson, Ramakrishna Vedantam
Hyperbolic Busemann Learning with Ideal Prototypes, NeurIPS 2021 Mina Ghadimi Atigh, Martin Keller-Ressel, Pascal Mettes
Rethinking the compositionality of point clouds through regularization in the hyperbolic space (NeurIPS 2022)
Antonio Montanaro, Diego Valsesia, Enrico Magli
HypLiLoc: Towards Effective LiDAR Pose Regression with Hyperbolic Fusion, CVPR 2023
Sijie Wang, Qiyu Kang, Rui She, Wei Wang, Kai Zhao, Yang Song, Wee Peng Tay
Clipped Hyperbolic Classifiers Are Super-Hyperbolic Classifiers, CVPR 2022
Yunhui Guo, Xudong Wang, Yubei Chen, Stella X. Yu
Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representations NeurIPS 2021
Joy Hsu, Jeffrey Gu, Gong-Her Wu, Wah Chiu, Serena Yeung
Learning Hyperbolic Representations of Topological Features ICLR 2021
Panagiotis Kyriakis, Iordanis Fostiropoulos, Paul Bogdan
Curvature Generation in Curved Spaces for Few-Shot Learning, ICCV 2021
Zhi* Gao, Yuwei Wu*, Yunde Jia, Mehrtash Harandi
Unsupervised Discovery of the Long-Tail in Instance Segmentation Using Hierarchical Self-Supervision, CVPR 2021
Zhenzhen Weng, Mehmet Giray Ogut, Shai Limonchik, Serena Yeung
Searching for Actions on the Hyperbole, CVPR 2020
Teng Long, Pascal Mettes, Heng Tao Shen, Cees Snoek
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition, ACM MM 2020
Wei Peng, Jingang Shi, Zhaoqiang Xia, Guoying Zhao
Meta Hyperbolic Networks for Zero-Shot Learning, Neurocomputing
Yan Xu, Lifu Mu, ZhongJi, Xiyao Liu, JungongHan
Poincaré ResNet, arxiv 2023
Max van Spengler, Erwin Berkhout, Pascal Mettes
HISum: Hyperbolic Interaction Model for Extractive Multi-Document Summarization, WWW 2023
Mingyang Song, Yi Feng, Liping Jing
Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classification, NeurIPS 2022 Oral (Spotlight)
K Grover, SM Angara, M Akhtar, T Chakraborty
Probing BERT in Hyperbolic Spaces. ICLR 2021
Boli Chen, Yao Fu, Guangwei Xu, Pengjun Xie, Chuanqi Tan, Mosha Chen, Liping Jing
Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network. SIGIR short paper 2021
Zheng Liu , Xiaohan Li , Zeyu You , Tao Yang , Wei Fan , Philip Yu
ANTHEM: Attentive Hyperbolic Entity Model for Product Search. WSDM 2022
Nurendra Choudhary , Nikhil Rao , Sumeet Katariya , Karthik Subbian , Chandan K. Reddy
Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text, ICDM 2019 Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake
Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering, WSDM 2018 Yi Tay, Luu Anh Tuan, Siu Cheung Hui
Contrastive Multi-view Hyperbolic Hierarchical Clustering for clustering, IJCAI 2022
Fangfei Lin, Bing Bai, Kun Bai, Yazhou Ren, Peng Zhao, Zenglin Xu
Hyperbolic Busemann Learning with Ideal Prototypes, NeurIPS 2021
Mina Ghadimi Atigh, Martin Keller-Ressel, Pascal Mettes
Unsupervised Hyperbolic Metric Learning, CVPR 2021
Jiexi Yan, Lei Luo, Cheng Deng, Heng Huang
Hyperbolic Contrastive Learning, arxiv
Yun Yue, Fangzhou Lin, Kazunori D Yamada, Ziming Zhang
A Quadtree for Hyperbolic Space, arxiv 2023
Sándor Kisfaludi-Bak, Geert van Wordragen
Dimensionality Selection for Hyperbolic Embeddings using Decomposed Normalized Maximum Likelihood Code-Length, arxiv 2023
Ryo Yuki, Yuichi Ike, Kenji Yamanishi
CO-SNE: Dimensionality Reduction and Visualization for Hyperbolic Data for embedding visualization, CVPR 2022
Yunhui Guo, Haoran Guo, Stella Yu
Wrapped Distributions on homogeneous Riemannian manifolds for hyperbolic sampling, arxiv 2022
Fernando Galaz-Garcia, Marios Papamichalis, Kathryn Turnbull, Simon Lunagomez, Edoardo Airoldi
HyperAid: Denoising in hyperbolic spaces for tree-fitting and hierarchical clustering for clustering, KDD 2022
Eli Chien, Puoya Tabaghi, Olgica Milenkovic
Hyperbolic Feature Augmentation via Distribution Estimation and Infinite Sampling on Manifolds NeurIPS 2022
Zhi Gao, Yuwei Wu, Yunde Jia, Mehrtash Harandi
Exploring Data Geometry for Continual Learning CVPR 2023
Zhi Gao, Chen Xu, Feng Li, Yunde Jia, Mehrtash Harandi, Yuwei Wu
Curvature-Adaptive Meta-Learning for Fast Adaptation to Manifold Data, TPAMI
Zhi Gao, Yuwei Wu, Mehrtash Harandi, and Yunde Jia