- Hypergraph Learning: Methods and Practices (TPAMI, 2022) [paper]
- More Recent Advances in (Hyper)Graph Partitioning (ACM Computing Surveys, 2022) [paper]
- A Survey on Hypergraph Representation Learning (ACM Computing Surveys, 2023) [paper]
- Exact Inference in High-order Structured Prediction (ICML, 2023) [paper]
- From Hypergraph Energy Functions to Hypergraph Neural Networks (ICML, 2023) [paper]
- Optimal LP Rounding and Linear-Time Approximation Algorithms for Clustering Edge-Colored Hypergraphs (ICML, 2023) [paper]
- Projected Tensor Power Method for Hypergraph Community Recovery (ICML, 2023) [paper]
- Nonlinear Feature Diffusion on Hypergraphs (ICML, 2022) [paper]
- Two Heads are Better Than One: Hypergraph-Enhanced Graph Reasoning for Visual Event Ratiocination (ICML, 2021) [paper]
- Random Walks on Hypergraphs with Edge-Dependent Vertex Weights (ICML, 2019) [paper]
- Molecular Hypergraph Grammar with Its Application to Molecular Optimization (ICML, 2019) [paper]
- Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering (ICML, 2018) [paper]
- Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method (ICML, 2017) [paper]
- CAT-Walk: Inductive Hypergraph Learning via Set Walks (NeurIPS, 2023) [paper]
- HyTrel: Hypergraph-enhanced Tabular Data Representation Learning (NeurIPS, 2023) [paper]
- Sheaf Hypergraph Networks (NeurIPS, 2023) [paper]
- SHINE: SubHypergraph Inductive Neural nEtwork (NeurIPS, 2022) [paper]
- Sparse Hypergraph Community Detection Thresholds in Stochastic Block Model (NeurIPS, 2022) [paper]
- Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative (NeurIPS, 2022) [paper]
- Hypergraph Propagation and Community Selection for Objects Retrieval (NeurIPS, 2021) [paper]
- Transformers Generalize DeepSets and Can be Extended to Graphs & Hypergraphs (NeurIPS, 2021) [paper]
- Finding Bipartite Components in Hypergraphs (NeurIPS, 2021) [paper]
- Edge Representation Learning with Hypergraphs (NeurIPS, 2021) [paper]
- Neural Message Passing for Multi-Relational Ordered and Recursive Hypergraphs (NeurIPS, 2020) [paper]
- HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs (NeurIPS, 2019) [paper]
- Inhomogeneous Hypergraph Clustering with Applications (NeurIPS, 2017) [paper]
- From Graphs to Hypergraphs: Hypergraph Projection and its Remediation (ICLR, 2024) [paper]
- Hypergraph Dynamic System (ICLR, 2024) [paper]
- HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs (ICLR, 2024) [paper]
- LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference (ICLR, 2024) [paper]
- Equivariant Hypergraph Diffusion Neural Operators (ICLR, 2023) [paper]
- Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework (ICLR, 2023) [paper]
- You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks (ICLR, 2022) [paper]
- Learning to Represent Action Values as a Hypergraph on the Action Vertices (ICLR, 2021) [paper]
- Hyper-SAGNN: a self-attention based graph neural network for hypergraphs (ICLR, 2020) [paper]
- Classification of Edge-dependent Labels of Nodes in Hypergraphs (KDD, 2023) [paper]
- Mining of Real-world Hypergraphs: Patterns, Tools, and Generators (KDD, 2023) [paper]
- Learning Causal Effects on Hypergraphs (KDD Best Paper, 2022) [paper]
- Core-periphery Models for Hypergraphs (KDD, 2022) [paper]
- Self-Supervised Hypergraph Transformer for Recommender Systems (KDD, 2022) [paper]
- Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation (KDD, 2022) [paper]
- Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding (KDD, 2022) [paper]
- H2MN: Graph Similarity Learning with Hierarchical Hypergraph Matching Networks (KDD, 2021) [paper]
- Structural Patterns and Generative Models of Real-world Hypergraphs (KDD, 2020) [paper]
- Minimizing Localized Ratio Cut Objectives in Hypergraphs (KDD, 2020) [paper]
- Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs (KDD, 2020) [paper]
- Hypergraph Clustering Based on PageRank (KDD, 2020) [paper]
- Dual Channel Hypergraph Collaborative Filtering (KDD, 2020) [paper]
- Hypergraph Convolutional Recurrent Neural Network (KDD, 2020) [paper]
- E-tail Product Return Prediction via Hypergraph-based Local Graph Cut (KDD, 2018) [paper]
- Spatio-Temporal Hypergraph Learning for Next POI Recommendation (SIGIR, 2023) [paper]
- Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation (SIGIR, 2023) [paper]
- Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network (SIGIR, 2023) [paper]
- HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer (SIGIR, 2023) [paper]
- Co-clustering Interactions via Attentive Hypergraph Neural Network (SIGIR, 2022) [paper]
- Hypergraph Contrastive Collaborative Filtering (SIGIR, 2022) [paper]
- Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation (SIGIR, 2022) [paper]
- DH-HGCN: Dual Homogeneity Hypergraph Convolutional Network for Multiple Social Recommendations (SIGIR, 2022) [paper]
- Communication Efficient Distributed Hypergraph Clustering (SIGIR, 2021) [paper]
- Next-item Recommendation with Sequential Hypergraphs (SIGIR, 2020) [paper]
- HyConvE: A Novel Embedding Model for Knowledge Hypergraph Link Prediction with Convolutional Neural Networks (WWW, 2023) [paper]
- Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation (WWW, 2023) [paper]
- Cut-matching Games for Generalized Hypergraph Ratio Cuts (WWW, 2023) [paper]
- Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation (WWW, 2023) [paper]
- IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search (WWW, 2022) [paper]
- MiDaS: Representative Sampling from Real-world Hypergraphs (WWW, 2022) [paper]
- Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning (WWW, 2021) [paper]
- Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks (WWW, 2021) [paper]
- Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation (WWW, 2021) [paper]
- How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators (WWW, 2021) [paper]
- How Much and When Do We Need Higher-order Information in Hypergraphs? A Case Study on Hyperedge Prediction (WWW, 2020) [paper]
- Clustering in graphs and hypergraphs with categorical edge labels (WWW, 2020) [paper]
- Revisiting User Mobility and Social Relationships in LBSNs: A Hypergraph Embedding Approach (WWW, 2019) [paper]
- Learning on Partial-Order Hypergraphs (WWW, 2018) [paper]
- Hypergraph Simultaneous Generators (AISTATS, 2022) [paper]
- Statistical and computational thresholds for the planted k-densest sub-hypergraph problem (AISTATS, 2022) [paper]
-
$𝐻𝑆^2$ : Active learning over hypergraphs with pointwise and pairwise queries (AISTATS, 2019) [paper] - Community Detection in Hypergraphs: Optimal Statistical Limit and Efficient Algorithms (AISTATS, 2018) [paper]
- Submodularity on Hypergraphs: From Sets to Sequences (AISTATS, 2018) [paper]
- Nested Named Entity Recognition as Building Local Hypergraphs (AAAI, 2023) [paper]
- Multi-Modal Knowledge Hypergraph for Diverse Image Retrieval (AAAI, 2023) [paper]
- Exploring Hypergraph of Earnings Call for Risk Prediction (AAAI, 2023) [paper]
- Hypergraph Modeling via Spectral Embedding Connection: Hypergraph Cut, Weighted Kernel k-Means, and Heat Kernel (AAAI, 2022) [paper]
- MS-HGAT: Memory-Enhanced Sequential Hypergraph Attention Network for Information Diffusion Prediction (AAAI, 2022) [paper]
- Adaptive Hypergraph Neural Network for Multi-Person Pose Estimation (AAAI, 2022) [paper]
- Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs (AAAI, 2021) [paper]
- Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach (AAAI, 2021) [paper]
- Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation (AAAI, 2021) [paper]
- The Impact of Selfishness in Hypergraph Hedonic Games (AAAI, 2020) [paper]
- Hypergraph Label Propagation Network (AAAI, 2020) [paper]
- Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds (AAAI, 2019) [paper]
- Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs (AAAI, 2019) [paper]
- Hypergraph Optimization for Multi-Structural Geometric Model Fitting (AAAI, 2019) [paper]
- Learning Non-Uniform Hypergraph for Multi-Object Tracking (AAAI, 2019) [paper]
- Hypergraph Neural Networks (AAAI, 2019) [paper]
- Hypergraph p-Laplacian: A Differential Geometry View (AAAI, 2018) [paper]
- Hypergraph Learning With Cost Interval Optimization (AAAI, 2018) [paper]
- Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation (IJCAI, 2023) [paper]
- Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning (IJCAI, 2023) [paper]
- Totally Dynamic Hypergraph Neural Networks (IJCAI, 2023) [paper]
- Multi-view Contrastive Learning Hypergraph Neural Network for Drug-Microbe-Disease Association Prediction (IJCAI, 2023) [paper]
- Hypertron: Explicit Social-Temporal Hypergraph Framework for Multi-Agent Forecasting (IJCAI, 2022) [paper]
- Hypergraph Structure Learning for Hypergraph Neural Networks (IJCAI, 2022) [paper]
- Online ECG Emotion Recognition for Unknown Subjects via Hypergraph-Based Transfer Learning (IJCAI, 2022) [paper]
- Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning (IJCAI, 2021) [paper]
- UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks (IJCAI, 2021) [paper]
- Semi-Dynamic Hypergraph Neural Network for 3D Pose Estimation (IJCAI, 2020) [paper]
- Knowledge Hypergraphs: Prediction Beyond Binary Relations (IJCAI, 2020) [paper]
- Two-Phase Hypergraph Based Reasoning with Dynamic Relations for Multi-Hop KBQA (IJCAI, 2020) [paper]
- Dynamic Hypergraph Neural Networks (IJCAI, 2019) [paper]
- Hypergraph Induced Convolutional Manifold Networks (IJCAI, 2019) [paper]
- Dynamic Hypergraph Structure Learning (IJCAI, 2018) [paper]
- Synchronisation Games on Hypergraphs (IJCAI, 2017) [paper]
- Vertex-Weighted Hypergraph Learning for Multi-View Object Classification (IJCAI, 2017) [paper]
- Adaptive Hypergraph Learning for Unsupervised Feature Selection (IJCAI, 2017) [paper]
- Lossy Compression of Pattern Databases Using Acyclic Random Hypergraphs (IJCAI, 2017) [paper]
- Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning (CIKM, 2023) [paper]
- Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph (CIKM, 2023) [paper]
- Seq-HyGAN: Sequence Classification via Hypergraph Attention Network (CIKM, 2023) [paper]
- Exploring Cohesive Subgraphs in Hypergraphs: The (k,g)-core Approach (CIKM, 2023) [paper]
- Semi-supervised Hypergraph Node Classification on Hypergraph Line Expansion (CIKM, 2022) [paper]
- Click-Through Rate Prediction with Multi-Modal Hypergraphs (CIKM, 2021) [paper]
- Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation (CIKM, 2021) [paper]
- Hyperbolic Hypergraphs for Sequential Recommendation (CIKM, 2021) [paper]
- HyperGraph Convolution Based Attributed HyperGraph Clustering (CIKM, 2021) [paper]
- Hypergraph Random Walks, Laplacians, and Clustering (CIKM, 2020) [paper]
- NHP: Neural Hypergraph Link Prediction (CIKM, 2020) [paper]
- Modeling Multi-way Relations with Hypergraph Embedding (CIKM, 2018) [paper]
- Computing Betweenness Centrality in B-hypergraphs (CIKM, 2017) [paper]
- Maintaining Densest Subsets Efficiently in Evolving Hypergraphs (CIKM, 2017) [paper]
- Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators (ICDM, 2022) [paper]
- THINK: Temporal Hypergraph Hyperbolic Network (ICDM, 2022) [paper]
- Hypergraph Convolutional Network for Group Recommendation (ICDM, 2021) [paper]
- THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting (ICDM, 2021) [paper]
- Hypergraph Ego-networks and Their Temporal Evolution (ICDM, 2021) [paper]
- HyperTeNet: Hypergraph and Transformer-based Neural Network for Personalized List Continuation (ICDM, 2021) [paper]
- Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting (ICDM, 2020) [paper]
- Evolution of Real-World Hypergraphs: Patterns and Models without Oracles (ICDM, 2020) [paper]
- Hypergraph Isomorphism Computation (TPAMI, 2024) [paper]
- HGNN+: General Hypergraph Neural Networks (TPAMI, 2023) [paper]
- Hypergraph Collaborative Network on Vertices and Hyperedges (TPAMI, 2023) [paper]
- Messages are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-Series Forecasting (TPAMI, 2023) [paper]
- Continual Image Deraining With Hypergraph Convolutional Networks (TPAMI, 2023) [paper]
- Generating Hypergraph-Based High-Order Representations of Whole-Slide Histopathological Images for Survival Prediction (TPAMI, 2023) [paper]
- Hypergraph-Based Multi-Modal Representation for Open-Set 3D Object Retrieval (TPAMI, 2023) [paper]
- Hypergraph Learning: Methods and Practices (TPAMI, 2022) [paper]
- Heterogeneous Hypergraph Variational Autoencoder for Link Prediction (TPAMI, 2022) [paper]
- Neural Graph Matching Network: Learning Lawler’s Quadratic Assignment Problem With Extension to Hypergraph and Multiple-Graph Matching (TPAMI, 2022) [paper]
- Learning on Hypergraphs With Sparsity (TPAMI, 2021) [paper]
- Searching for Representative Modes on Hypergraphs for Robust Geometric Model Fitting (TPAMI, 2019) [paper]
- Clustering with Hypergraphs: The Case for Large Hyperedges (TPAMI, 2017) [paper]
- An Efficient Multilinear Optimization Framework for Hypergraph Matching (TPAMI, 2017) [paper]
- Exploiting Hierarchical Dense Structures on Hypergraphs for Multi-Object Tracking (TPAMI, 2016) [paper]
- HyperISO: Efficiently Searching Subgraph Containment in Hypergraphs (TKDE, 2023) [paper]
- Adaptive Hypergraph Auto-Encoder for Relational Data Clustering (TKDE, 2023) [paper]
- Penalized Flow Hypergraph Local Clustering (TKDE, 2023) [paper]
- Hypergraph Representation for Detecting 3D Objects From Noisy Point Clouds (TKDE, 2023) [paper]
- Self-Supervised Hypergraph Representation Learning for Sociological Analysis (TKDE, 2023) [paper]
- Efficiently Counting Triangles for Hypergraph Streams by Reservoir-Based Sampling (TKDE, 2023) [paper]
- Hypergraph Partitioning With Embeddings (TKDE, 2022) [paper]
- Distributed Hypergraph Processing Using Intersection Graphs (TKDE, 2022) [paper]
- Data Representation by Joint Hypergraph Embedding and Sparse Coding (TKDE, 2022) [paper]
- HyperISO: Efficiently Searching Subgraph Containment in Hypergraphs (TKDE, 2022) [paper]
- Hypergraph Representation for Detecting 3D Objects from Noisy Point Clouds (TKDE, 2022) [paper]
- LBSN2Vec++: Heterogeneous Hypergraph Embedding for Location-Based Social Networks (TKDE, 2022) [paper]
- Adaptive Hypergraph Auto-Encoder for Relational Data Clustering (TKDE, 2021) [paper]
- Re-Revisiting Learning on Hypergraphs: Confidence Interval, Subgradient Method, and Extension to Multiclass (TKDE, 2020) [paper]
- HyperX: A Scalable Hypergraph Framework (TKDE, 2019) [paper]
- Dual Hypergraph Regularized PCA for Biclustering of Tumor Gene Expression Data (TKDE, 2019) [paper]
- Malevolent Activity Detection with Hypergraph-Based Models (TKDE, 2017) [paper]
- Brain Network Analysis of Schizophrenia Patients Based on Hypergraph Signal Processing (TIP, 2023) [paper]
- Multimodal Remote Sensing Image Segmentation With Intuition-Inspired Hypergraph Modeling (TIP, 2023) [paper]
- An Efficient Hypergraph Approach to Robust Point Cloud Resampling (TIP, 2022) [paper]
- Big-Hypergraph Factorization Neural Network for Survival Prediction From Whole Slide Image (TIP, 2022) [paper]
- Hypergraph Spectral Analysis and Processing in 3D Point Cloud (TIP, 2021) [paper]
- Hypergraph Neural Network for Skeleton-Based Action Recognition (TIP, 2021) [paper]
- Multi-Scale Representation Learning on Hypergraph for 3D Shape Retrieval and Recognition (TIP, 2021) [paper]
- Correntropy-Induced Robust Low-Rank Hypergraph (TIP, 2019) [paper]
- Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking (TIP, 2019) [paper]
- Inductive Multi-Hypergraph Learning and Its Application on View-Based 3D Object Classification (TIP, 2018) [paper]
- Joint Hypergraph Learning for Tag-Based Image Retrieval (TIP, 2018) [paper]
- Elastic Net Hypergraph Learning for Image Clustering and Semi-Supervised Classification (TIP, 2017) [paper]
- Central-Smoothing Hypergraph Neural Networks for Predicting Drug–Drug Interactions (TNNLS, 2023) [paper]
- Modeling High-Order Relationships: Brain-Inspired Hypergraph-Induced Multimodal-Multitask Framework for Semantic Comprehension (TNNLS, 2023) [paper]
- Music Recommendation via Hypergraph Embedding (TNNLS, 2023) [paper]
- Hypergraph Structural Information Aggregation Generative Adversarial Networks for Diagnosis and Pathogenetic Factors Identification of Alzheimer’s Disease With Imaging Genetic Data (TNNLS, 2022) [paper]
- Multi-Atlas Segmentation of Anatomical Brain Structures Using Hierarchical Hypergraph Learning (TNNLS, 2020) [paper]
- Hypergraph-Induced Convolutional Networks for Visual Classification (TNNLS, 2019) [paper]
- Learning to Map Social Network Users by Unified Manifold Alignment on Hypergraph (TNNLS, 2018) [paper]
- Person Re-identification by Multi-hypergraph Fusion (TNNLS, 2017) [paper]
- Prior-Guided Adversarial Learning With Hypergraph for Predicting Abnormal Connections in Alzheimer’s Disease (TCYB, 2024) [paper]
- Cost-Sensitive Hypergraph Learning With F-Measure Optimization (TCYB, 2023) [paper]
- Correntropy-Based Hypergraph Regularized NMF for Clustering and Feature Selection on Multi-Cancer Integrated Data (TCYB, 2021) [paper]
- Feature Learning Using Spatial-Spectral Hypergraph Discriminant Analysis for Hyperspectral Image (TCYB, 2019) [paper]
- Adaptive Discrete Hypergraph Matching (TCYB, 2018) [paper]
- Geometric Hypergraph Learning for Visual Tracking (TCYB, 2017) [paper]
- Unsupervised Topic Hypergraph Hashing for Efficient Mobile Image Retrieval (TCYB, 2017) [paper]
- Automatic Hypergraph Generation for Enhancing Recommendation with Sparse Optimization (TMM, 2023) [paper]
- Adaptive Multi-Hypergraph Convolutional Networks for 3D Object Classification (TMM, 2023) [paper]
- A Universal Quaternion Hypergraph Network for Multimodal Video Question Answering (TMM, 2023) [paper]
- Object Cosegmentation in Noisy Videos With Multilevel Hypergraph (TMM, 2021) [paper]
- Cross-Modality Microblog Sentiment Prediction via Bi-Layer Multimodal Hypergraph Learning (TMM, 2019) [paper]
- Adaptive Hypergraph Embedded Semi-Supervised Multi-Label Image Annotation (TMM, 2019) [paper]
- Context-Aware Hypergraph Modeling for Re-identification and Summarization (TMM, 2016) [paper]
- Sparse random hypergraphs: Non-backtracking spectra and community detection (FOCS, 2022) [paper]
- Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models (FOCS, 2022) [paper]
- Spectral Hypergraph Sparsifiers of Nearly Linear Size (FOCS, 2021) [paper]
- Hypergraph k-cut for fixed k in deterministic polynomial time (FOCS, 2020) [paper]
- Near-linear Size Hypergraph Cut Sparsifiers (FOCS, 2020) [paper]
- Distributed Local Approximation Algorithms for Maximum Matching in Graphs and Hypergraphs (FOCS, 2019) [paper]
- New Notions and Constructions of Sparsification for Graphs and Hypergraphs (FOCS, 2019) [paper]
- The Average-Case Complexity of Counting Cliques in Erdős-Rényi Hypergraphs (FOCS, 2019) [paper]
- The Sketching Complexity of Graph and Hypergraph Counting (FOCS, 2018) [paper]
- A Characterization of Testable Hypergraph Properties (FOCS, 2017) [paper]
- Deterministic Distributed Edge-Coloring via Hypergraph Maximal Matching (FOCS, 2017) [paper]
- Conflict-free hypergraph matchings (SODA, 2023) [paper]
- Zigzagging through acyclic orientations of chordal graphs and hypergraphs (SODA, 2023)
- A simple and sharper proof of the hypergraph Moore bound (SODA, 2023) [paper]
- Distributed Maximal Matching and Maximal Independent Set on Hypergraphs (SODA, 2023) [paper]
- On the complexity of binary polynomial optimization over acyclic hypergraphs (SODA, 2022) [paper]
- Approximate Hypergraph Vertex Cover and generalized Tuza's conjecture (SODA, 2022) [paper]
- Deterministic enumeration of all minimum k-cut-sets in hypergraphs for fixed k (SODA, 2022) [paper]
- Min-max Partitioning of Hypergraphs and Symmetric Submodular Functions (SODA, 2021) [paper]
- Non-linear Hamilton cycles in linear quasi-random hypergraphs (SODA, 2021) [paper]
- Finding Perfect Matchings in Dense Hypergraphs (SODA, 2020) [paper]
- A Tale of Santa Claus, Hypergraphs and Matroids (SODA, 2020) [paper]
- Factors and loose Hamilton cycles in sparse pseudo-random hypergraphs (SODA, 2020) [paper]
- Spectral Sparsification of Hypergraphs (SODA, 2019) [paper]
- Minimum Cut and Minimum k-Cut in Hypergraphs via Branching Contractions (SODA, 2019) [paper]
- Derandomized concentration bounds for polynomials, and hypergraph maximal independent set (SODA, 2018) [paper]
- Hypergraph k-Cut in Randomized Polynomial Time (SODA, 2018) [paper]
- Computing minimum cuts in hypergraphs (SODA, 2017) [paper]
- Random Contractions and Sampling for Hypergraph and Hedge Connectivity (SODA, 2017) [paper]
- Tight Algorithms for Vertex Cover with Hard Capacities on Multigraphs and Hypergraphs (SODA, 2017) [paper]
- The complexity of approximately counting in 2-spin systems on k-uniform bounded-degree hypergraphs (SODA, 2016) [paper]
- An Algorithmic Hypergraph Regularity Lemma (SODA, 2016) [paper]
- Finding Perfect Matchings in Bipartite Hypergraphs (SODA, 2016) [paper]
- Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification (STOC, 2023) [paper]
- Cheeger Inequalities for Directed Graphs and Hypergraphs using Reweighted Eigenvalues (STOC, 2023) [paper]
- Algorithmic Applications of Hypergraph and Partition Containers (STOC, 2023) [paper]
- Spectral Hypergraph Sparsification via Chaining (STOC, 2023) [paper]
- Towards tight bounds for spectral sparsification of hypergraphs (STOC, 2021) [paper]
- Extractors for adversarial sources via extremal hypergraphs (STOC, 2020) [paper]
- Counting hypergraph colourings in the local lemma regime (STOC, 2018) [paper]
- Community Detection in the Hypergraph SBM: Optimal Recovery Given the Similarity Matrix (COLT, 2023) [paper]
- Weak Recovery Threshold for the Hypergraph Stochastic Block Model (COLT, 2023) [paper]
- Learning Low Degree Hypergraphs (COLT, 2022) [paper]
- Open Problem: Average-Case Hardness of Hypergraphic Planted Clique Detection (COLT, 2020) [paper]
- Counting Simplices in Hypergraph Streams (ESA, 2022) [paper]
- Fully Dynamic Set Cover via Hypergraph Maximal Matching: An Optimal Approximation Through a Local Approach (ESA, 2021) [paper]
- The Minimization of Random Hypergraphs (ESA, 2020) [paper]
- Distributed Algorithms for Matching in Hypergraphs (ESA, 2020) [paper]
- Dense Peelable Random Uniform Hypergraphs (ESA, 2019) [paper]
- Evaluation of a Flow-Based Hypergraph Bipartitioning Algorithm (ESA, 2019) [paper]
- Clustering in Hypergraphs to Minimize Average Edge Service Time (ESA, 2017) [paper]
- Spectral Properties of Hypergraph Laplacian and Approximation Algorithms (JACM, 2018) [paper]
- Augmented Sparsifiers for Generalized Hypergraph Cuts (JMLR, 2023) [paper]
- Knowledge Hypergraph Embedding Meets Relational Algebra (JMLR, 2023) [paper]
- Nonparametric modeling of higher-order interactions via hypergraphons (JMLR, 2021) [paper]
- Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques (JMLR, 2017) [paper]
- Pliable Index Coding via Conflict-Free Colorings of Hypergraphs (TIT, 2024) [paper]
- Strong Consistency of Spectral Clustering for the Sparse Degree-Corrected Hypergraph Stochastic Block Model (TIT, 2023) [paper]
- Exact Recovery in the General Hypergraph Stochastic Block Model (TIT, 2023) [paper]
- Limitations on Transversal Gates for Hypergraph Product Codes (TIT, 2022) [paper]
- ReShape: A Decoder for Hypergraph Product Codes (TIT, 2022) [paper]
- On Some Distributed Scheduling Algorithms for Wireless Networks With Hypergraph Interference Models (TIT, 2021) [paper]
- Motif and Hypergraph Correlation Clustering (TIT, 2020) [paper]
- Community Recovery in Hypergraphs (TIT, 2019) [paper]
- On the Minimax Misclassification Ratio of Hypergraph Community Detection (TIT, 2019) [paper]
- Centralized Coded Caching Schemes: A Hypergraph Theoretical Approach (TIT, 2018) [paper]
- New Lower Bounds for Secure Codes and Related Hash Families: A Hypergraph Theoretical Approach (TIT, 2017) [paper]
- Mining of Real-world Hypergraphs: Patterns, Tools, and Generators (CIKM, 2022) [website]
- Multimodal deep learning on hypergraphs (University of Amsterdam, 2022) [PhD Thesis]
| Cora | Citeseer | Pubmed | Cora-CA | DBLP-CA | Zoo | 20News | |
|---|---|---|---|---|---|---|---|
| #Vertex | 2708 | 3312 | 19717 | 2708 | 41302 | 101 | 16242 |
| #Hyperedge | 1579 | 1079 | 7963 | 1072 | 22363 | 43 | 100 |
| #Feature | 1433 | 3703 | 500 | 1433 | 1425 | 16 | 100 |
| #Class | 7 | 6 | 3 | 7 | 6 | 7 | 4 |
| Max Hyperedge Size | 5 | 26 | 171 | 43 | 202 | 93 | 2241 |
| Mushroom | NTU2012 | ModelNet40 | Yelp | House | Walmart | |
|---|---|---|---|---|---|---|
| #Vertex | 8124 | 2012 | 12311 | 50758 | 1290 | 88860 |
| #Hyperedge | 298 | 2012 | 12311 | 679302 | 341 | 69906 |
| #Feature | 22 | 100 | 100 | 1862 | 100 | 100 |
| #Class | 2 | 67 | 40 | 9 | 2 | 11 |
| Max Hyperedge Size | 1808 | 5 | 5 | 2838 | 81 | 25 |
Hypergraph node classification dataset is available at https://github.com/jianhao2016/AllSet
Hypergraph clustering dataset is available at https://sites.google.com/view/panli-purdue/datasets
Hypergraph partitioning dataset is available at https://kahypar.org/
PyTorch Geometric: https://pytorch-geometric.readthedocs.io/en/latest/modules/nn.html#convolutional-layers (Hypergraph Convolution Network)
DeepHypergraph: https://github.com/iMoonLab/DeepHypergraph (Hypergraph Neural Networks)
OpenHGNN: https://github.com/BUPT-GAMMA/OpenHGNN (Heterogeneous Graph Neural Network)
HyperNetX: https://github.com/pnnl/HyperNetX (Community Detection, Clustering, Generation, Visualization)
KaHyPar: https://github.com/kahypar/kahypar (Hypergraph Partitioning)
HAT: https://github.com/Jpickard1/Hypergraph-Analysis-Toolbox (Hypergraph Analysis)
Hypergraph: https://github.com/yamafaktory/hypergraph (Data Structure)
XGI: https://github.com/xgi-org/xgi (Hypergraph Group Interaction)
Hypergraph Embedding: https://paperswithcode.com/task/hypergraph-embedding
Hypergraph Matching: https://paperswithcode.com/task/hypergraph-matching
Hypergraph Representations: https://paperswithcode.com/task/hypergraph-representations
Hypergraph Partitioning: https://paperswithcode.com/task/hypergraph-partitioning
