SS-L14.3
A BAYESIAN APPROACH TO HIGH-ORDER LINK PREDICTION
Georgios Vasileios Karanikolas, University of Minnesota, United States of America; Alba Pagès-Zamora, Universitat Politècnica de Catalunya, Spain; Georgios B. Giannakis, University of Minnesota, United States of America
Session:
SS-L14: Topological Signal Processing over Higher-order Networks Lecture
Track:
Special Sessions
Location:
Room E8
Presentation Time:
Thu, 18 Apr, 17:10 - 17:30 (UTC +9)
Session Co-Chairs:
Elvin Isufi, Delft University of Technology and Sundeep Prabhakar Chepuri, Indian Institute of Science and Paolo Di Lorenzo, La Sapienza University of Rome
Session SS-L14
SS-L14.1: TOPOLOGICAL NEURAL NETWORKS OVER THE AIR
Simone Fiorellino, Claudio Battiloro, Paolo Di Lorenzo, Sapienza University of Rome, Italy
SS-L14.2: Sampling and Recovery of Signals over Product Cell Structures
Thummaluru Siddartha Reddy, Sundeep Prabhakar Chepuri, Indian Institute of Science, India
SS-L14.3: A BAYESIAN APPROACH TO HIGH-ORDER LINK PREDICTION
Georgios Vasileios Karanikolas, University of Minnesota, United States of America; Alba Pagès-Zamora, Universitat Politècnica de Catalunya, Spain; Georgios B. Giannakis, University of Minnesota, United States of America
SS-L14.4: SC-MAD: MIXTURES OF HIGHER-ORDER NETWORKS FOR DATA AUGMENTATION
Madeline Navarro, Santiago Segarra, Rice University, United States of America
SS-L14.5: Hypergraph-MLP: Learning On Hypergraphs Without Message Passing
Bohan Tang, University of Oxford, United Kingdom of Great Britain and Northern Ireland; Siheng Chen, Shanghai Jiao Tong University, Shanghai AI Laboratory, China; Xiaowen Dong, University of Oxford, United Kingdom of Great Britain and Northern Ireland
SS-L14.6: HODGE-AWARE CONTRASTIVE LEARNING
Alexander Möllers, Delft University of Technology, Netherlands; Alexander Immer, ETH Zürich, Switzerland; Vincent Fortuin, Helmholtz AI, Germany; Elvin Isufi, Delft University of Technology, Switzerland
Contacts