Higher-Order-Network

This is a collection of research about higher-order network (continuously updated).

1. Higher-Order Systems

• Battiston, Federico, and Giovanni Petri. "Higher-Order Systems." (2022). paper link
• Bianconi, Ginestra. HIGHER ORDER NETWORKS: An Introduction to Simplicial Complexes. Cambridge University Press, 2021. paper link
• Battiston, Federico, et al. "Networks beyond pairwise interactions: structure and dynamics." Physics Reports 874 (2020): 1-92. paper link
• Battiston, Federico, et al. "The physics of higher-order interactions in complex systems." Nature Physics 17.10 (2021): 1093-1098. paper link
• Bick, Christian, et al. "What are higher-order networks?" arXiv preprint arXiv:2104.11329 (2021). paper link
• Torres, Leo, et al. "The why, how, and when of representations for complex systems." SIAM Review 63.3 (2021): 435-485. paper link
• Benson, Austin R., David F. Gleich, and Desmond J. Higham. "Higher-order network analysis takes off, fueled by classical ideas and new data." arXiv preprint arXiv:2103.05031 (2021). paper link

2. Higher-Order Interaction Modeling

• Kovalenko, Kiriil, Irene Sendiña-Nadal, Nagi Khalil, Alex Dainiak, Daniil Musatov, Andrei M. Raigorodskii, Karin Alfaro-Bittner, Baruch Barzel, and Stefano Boccaletti. "Growing scale-free simplices." Communications Physics 4, no. 1 (2021): 1-9.
• Bobrowski, Omer, and Dmitri Krioukov. "Random Simplicial Complexes: Models and Phenomena." arXiv preprint arXiv:2105.12914 (2021).
• Ghoshal, Gourab, et al. "Random hypergraphs and their applications." Physical Review E 79.6 (2009): 066118. Ghoshal, G., Zlatic, V., Caldarelli, G. & Newman, M. E.. Physical Review E 79, 066118, doi:10.1103/PhysRevE.79.066118 (2009).
• Costa, Armindo, and Michael Farber. "Random simplicial complexes." Configuration spaces. Springer, Cham, 2016. 129-153.
• Courtney, Owen T., and Ginestra Bianconi. "Generalized network structures: The configuration model and the canonical ensemble of simplicial complexes." Physical Review E 93.6 (2016): 062311.
• Yen, Tzu-Chi. "Construction of simplicial complexes with prescribed degree-size sequences." Physical Review E 104.4 (2021): L042303.
• Zuev, Konstantin, Or Eisenberg, and Dmitri Krioukov. "Exponential random simplicial complexes." Journal of Physics A: Mathematical and Theoretical 48.46 (2015): 465002.
• Rosvall, Martin, et al. "Memory in network flows and its effects on spreading dynamics and community detection." Nature communications 5.1 (2014): 1-13.
• Xu, Jian, Thanuka L. Wickramarathne, and Nitesh V. Chawla. "Representing higher-order dependencies in networks." Science advances 2.5 (2016): e1600028.
• Scholtes, Ingo, Nicolas Wider, and Antonios Garas. "Higher-order aggregate networks in the analysis of temporal networks: path structures and centralities." The European Physical Journal B 89, no. 3 (2016): 1-15., 89(3), 1-15.
• Lambiotte, Renaud, Martin Rosvall, and Ingo Scholtes. "From networks to optimal higher-order models of complex systems." Nature physics 15.4 (2019): 313-320.

3. Important Higher-Order Structure———— Cycles, Cliques and Cavities

• Lee G, Ko J, Shin K. Hypergraph motifs: concepts, algorithms, and discoveries[J]. Proceedings of the VLDB Endowment, 2020, 13(12): 2256-2269.
• Li X, Cheng R, Chang K C C, et al. On analyzing graphs with motif-paths[J]. Proceedings of the VLDB Endowment, 2021, 14(6): 1111-1123.
• Shi, Dinghua, et al. "Searching for optimal network topology with best possible synchronizability." IEEE Circuits and Systems Magazine 13.1 (2013): 66-75. https://ieeexplore.ieee.org/abstract/document/6468141
• Shi, D., Lü, L. & Chen, G. "Totally homogeneous networks." Natl. Sci. Rev. 6. 962–969 (2019). https://academic.oup.com/nsr/article/6/5/962/5435524
• Shi, D., Chen, G., et al. "Computing cliques and cavities in networks. "Communications Physics. 4, 249 (2021). https://www.nature.com/articles/s42005-021-00748-4
• Reimann, Michael W., et al. "Cliques of neurons bound into cavities provide a missing link between structure and function." Frontiers in computational neuroscience(2017): 48. https://www.frontiersin.org/articles/10.3389/fncom.2017.00048/full?fbclid=IwAR3pRFXTWZ8soPgEhyRLT2AYT5nFjIA68uMVbcb-e3jJacUXMF5cV1ko748
• Gebhart, Thomas, and Russell J. Funk. "The emergence of higher-order structure in scientific and technological knowledge networks." arXiv preprint arXiv:2009.13620 (2020). https://arxiv.org/pdf/2009.13620

4. Important Node(s) Identification in Higher-Order Interaction Networks

• Battiston, Federico, et al. "Networks beyond pairwise interactions: structure and dynamics." Physics Reports 874 (2020): 1-92.
• Fan, Tianlong, et al. "Characterizing cycle structure in complex networks." Communications Physics 4.1 (2021): 1-9.
• Tudisco, Francesco, and Desmond J. Higham. "Node and edge nonlinear eigenvector centrality for hypergraphs." Communications Physics 4.1 (2021): 1-10.
• Kovalenko, Kirill, et al. "Vector Centrality in Networks with Higher-Order Interactions." arXiv preprint arXiv:2108.13846 (2021).
• Aktas, Mehmet Emin, et al. "Identifying critical higher-order interactions in complex networks." Scientific reports 11.1 (2021): 1-11.
• Wang, Pei, Jinhu Lü, and Xinghuo Yu. "Identification of important nodes in directed biological networks: A network motif approach." PloS one 9.8 (2014): e106132.

5. Link Prediction in Higher-Order Interaction Networks

• Benson, Austin R., Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. "Simplicial closure and higher-order link prediction." Proceedings of the National Academy of Sciences 115, no. 48 (2018): E11221-E11230. paper link
• Coutino, Mario, Georgios V. Karanikolas, Geert Leus, and Georgios B. Giannakis. "Self-driven graph volterra models for higher-order link prediction." In ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3887-3891. IEEE, 2020. paper link
• Chavan, Neeraj, and Katerina Potika. "Higher-order link prediction using triangle embeddings." In 2020 IEEE International Conference on Big Data (Big Data), pp. 4535-4544. IEEE, 2020. paper link
• Xu Y, Rockmore D, Kleinbaum A M. Hyperlink prediction in hypernetworks using latent social features[C]//International Conference on Discovery Science. Springer, Berlin, Heidelberg, 2013: 324-339. paper link
• Li D, Xu Z, Li S, et al. Link prediction in social networks based on hypergraph[C]//Proceedings of the 22nd international conference on world wide web. 2013: 41-42. paper link

6. Community Detection in Higher-Order Interaction Networks

• Hu L, Pan X, Yan H, et al. Exploiting higher-order patterns for community detection in attributed graphs[J]. Integrated Computer-Aided Engineering, 2021, 28(2): 207-218.
• Li P Z, Huang L, Wang C D, et al. Community detection by motif-aware label propagation[J]. ACM Transactions on Knowledge Discovery from Data (TKDD), 2020, 14(2): 1-19.
• Kumar S, Panda B S, Aggarwal D. Community detection in complex networks using network embedding and gravitational search algorithm[J]. Journal of Intelligent Information Systems, 2021, 57(1): 51-72.
• Huang L, Wang C D, Chao H Y. HM-Modularity: A harmonic motif modularity approach for multi-layer network community detection[J]. IEEE Transactions on Knowledge and Data Engineering, 2019, 33(6): 2520-2533.
• Chien I E, Lin C Y, Wang I H. On the minimax misclassification ratio of hypergraph community detection[J]. IEEE Transactions on Information Theory, 2019, 65(12): 8095-8118.
• Li P Z, Huang L, Wang C D, et al. Edmot: An edge enhancement approach for motif-aware community detection[C]//Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining. 2019: 479-487.
• Huang L, Chao H Y, Xie Q. MuMod: A micro-unit connection approach for hybrid-order community detection[C]//Proceedings of the AAAI conference on artificial intelligence. 2020, 34(01): 107-114.
• Amburg I, Veldt N, Benson A. Clustering in graphs and hypergraphs with categorical edge labels[C]//Proceedings of The Web Conference 2020. 2020: 706-717.
• Takai Y, Miyauchi A, Ikeda M, et al. Hypergraph clustering based on pagerank[C]//Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2020: 1970-1978.
• Huang L, Wang C D, Chao H Y. HM-Modularity: A harmonic motif modularity approach for multi-layer network community detection[J]. IEEE Transactions on Knowledge and Data Engineering, 2019, 33(6): 2520-2533.
• Gao Y, Yu X, Zhang H. Graph clustering using triangle-aware measures in large networks[J]. Information Sciences, 2022, 584: 618-632.
• Gao Y, Zhang H, Yu X. Higher-Order Community Detection: On Information Degeneration and Its Elimination[J]. IEEE/ACM Transactions on Networking, 2022.
• Li C, Tang Y, Tang Z, et al. Motif‐based embedding label propagation algorithm for community detection[J]. International Journal of Intelligent Systems, 2022, 37(3): 1880-1902.

7. Hypergraph reconstruction

• Young J G, Petri G, Peixoto T P. Hypergraph reconstruction from network data[J]. Communications Physics, 2021, 4(1): 1-11.

8. Hypergraph learning

• Feng, Yifan, et al. "Hypergraph neural networks." AAAI (2019).
• Gao Y, Zhang Z, Lin H, et al. Hypergraph learning: Methods and practices[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.
• Huang J, Yang J. Unignn: a unified framework for graph and hypergraph neural networks[J]. arXiv preprint arXiv:2105.00956, 2021.
• Wu H, Ng M K. Hypergraph Convolution on Nodes-Hyperedges Network for Semi-Supervised Node Classification[J]. ACM Transactions on Knowledge Discovery from Data (TKDD), 2022, 16(4): 1-19.
• Xia L, Huang C, Xu Y, et al. Hypergraph contrastive collaborative filtering[C]//Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2022: 70-79.
• Chien, Eli et al. “You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.” ICLR (2022).
• Ebli, Stefania et al. “Simplicial Neural Networks.” ArXiv abs/2010.03633 (2020): n. pag.
• Saebi, Mandana et al. “HONEM: Learning Embedding for Higher Order Networks.” Big data 8 4 (2020): 255-269 .
• Huang, Jie et al. “Hyper2vec: Biased Random Walk for Hyper-network Embedding.” DASFAA (2019).
• Zhang, Ruochi et al. “Hyper-SAGNN: a self-attention based graph neural network for hypergraphs.” ICLR (2020): n. pag.
• Bai S, Zhang F, Torr P H S. Hypergraph convolution and hypergraph attention[J]. Pattern Recognition, 2021, 110: 107637.
• Choe M, Kim S, Yoo J, et al. Classification of edge-dependent labels of nodes in hypergraphs[C]//Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2023: 298-309.

9. Hypergraph spreading

• Iacopini, Iacopo, Giovanni Petri, Alain Barrat, and Vito Latora. 2019NC "Simplicial models of social contagion."
• Matamalas, Joan T., Sergio Gómez, and Alex Arenas. "Abrupt phase transition of epidemic spreading in simplicial complexes." Physical Review Research 2.1 (2020): 012049.
• Barrat, Alain, Guilherme Ferraz de Arruda, Iacopo Iacopini, and Yamir Moreno. "Social contagion on higher-order structures." arXiv preprint arXiv:2103.03709 (2021).
• Chowdhary, S., Kumar, A., Cencetti, G., Iacopini, I. and Battiston, F., 2021. "Simplicial contagion in temporal higher-order networks. Journal of Physics: Complexity.", 2(3), p.035019.
• Li, Z., Deng, Z., Han, Z., Alfaro-Bittner, K., Barzel, B. and Boccaletti, S., 2021. "Contagion in simplicial complexes". Chaos, Solitons & Fractals, 152, p.111307.
• Jhun, Bukyoung. "Effective epidemic containment strategy in hypergraphs." Physical Review Research 3.3 (2021): 033282.
• St-Onge, Guillaume, et al. "Universal nonlinear infection kernel from heterogeneous exposure on higher-order networks." Physical Review Letters 127.15 (2021): 158301.
• Landry, Nicholas W., and Juan G. Restrepo. "The effect of heterogeneity on hypergraph contagion models." Chaos: An Interdisciplinary Journal of Nonlinear Science 30.10 (2020): 103117.
• Wang, Dong, et al. "Simplicial SIRS epidemic models with nonlinear incidence rates." Chaos: An Interdisciplinary Journal of Nonlinear Science 31.5 (2021): 053112.
• De Arruda, Guilherme Ferraz, Giovanni Petri, and Yamir Moreno. "Social contagion models on hypergraphs." Physical Review Research 2.2 (2020): 023032.

10. Evolutionary games in higher-order networks

• Alvarez-Rodriguez, Unai, Federico Battiston, Guilherme Ferraz de Arruda, Yamir Moreno, Matjaž Perc, and Vito Latora. "Evolutionary dynamics of higher-order interactions in social networks." Nature Human Behaviour 5, no. 5 (2021): 586-595.
• Guo, H., D. Jia, I. Sendiña-Nadal, M. Zhang, Z. Wang, X. Li, K. Alfaro-Bittner, Y. Moreno, and S. Boccaletti. "Evolutionary games on simplicial complexes." Chaos, Solitons & Fractals 150 (2021): 111103.
• Civilini, Andrea, Nejat Anbarci, and Vito Latora. "Evolutionary Game Model of Group Choice Dilemmas on Hypergraphs." Physical review letters 127.26 (2021): 268301.
• Kumar, Aanjaneya, et al. "Evolution of honesty in higher-order social networks." Physical Review E 104.5 (2021): 054308.

11. Synchronization in higher-order networks

• Tanaka, Takuma, and Toshio Aoyagi. "Multistable attractors in a network of phase oscillators with three-body interactions." Physical Review Letters 106.22 (2011): 224101.
• Skardal, Per Sebastian, and Alex Arenas. "Abrupt desynchronization and extensive multistability in globally coupled oscillator simplexes." Physical review letters 122.24 (2019): 248301.
• Lucas, Maxime, Giulia Cencetti, and Federico Battiston. "Multiorder Laplacian for synchronization in higher-order networks." Physical Review Research 2.3 (2020): 033410.
• Millán, Ana P., Joaquín J. Torres, and Ginestra Bianconi. "Explosive higher-order Kuramoto dynamics on simplicial complexes." Physical Review Letters 124.21 (2020): 218301.
• Gambuzza, Lucia Valentina, et al. "Stability of synchronization in simplicial complexes." Nature communications 12.1 (2021): 1-13.
• Skardal, Per Sebastian, et al. "Higher-order interactions can better optimize network synchronization." Physical Review Research 3.4 (2021): 043193.
• Tang, Ying, Dinghua Shi, and Linyuan Lü. "Optimizing higher-order network topology for synchronization of coupled phase oscillators." Communications Physics 5.1 (2022): 1-12.
• Chen, Guanrong. "Searching for Best Network Topologies with Optimal Synchronizability: A Brief Review." IEEE/CAA Journal of Automatica Sinica 9.4 (2022): 573-577.
• Zhang, Yuanzhao, Maxime Lucas, and Federico Battiston. "Do higher-order interactions promote synchronization?." arXiv preprint arXiv:2203.03060 (2022).

12. Higher-order networks-based applications in science of science and human brain network

• Patania, Alice, Giovanni Petri, and Francesco Vaccarino. "The shape of collaborations." EPJ Data Science 6 (2017): 1-16.
• Gebhart, Thomas, and Russell J. Funk. "The emergence of higher-order structure in scientific and technological knowledge networks." arXiv preprint arXiv:2009.13620 (2020).
• Benson, Austin R., Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. "Simplicial closure and higher-order link prediction." Proceedings of the National Academy of Sciences 115, no. 48 (2018): E11221-E11230.
• Giusti, Chad, Robert Ghrist, and Danielle S. Bassett. "Two’s company, three (or more) is a simplex." Journal of computational neuroscience 41.1 (2016): 1-14.
• Sizemore, Ann E., Chad Giusti, Ari Kahn, Jean M. Vettel, Richard F. Betzel, and Danielle S. Bassett. "Cliques and cavities in the human connectome." Journal of computational neuroscience 44, no. 1 (2018): 115-145.
• Lynn, Christopher W., and Danielle S. Bassett. "The physics of brain network structure, function and control." Nature Reviews Physics 1, no. 5 (2019): 318-332.