Technical Program

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SS-L23: Deep Graph Learning

Session Type: Lecture
Time: Friday, 8 May, 08:00 - 10:00
Location: On-Demand
Virtual Session: View on Virtual Platform
Session Chairs: Sundeep Prabhakar Chepuri, Indian Institute of Science, Antonio G. Marques, King Juan Carlos University, Santiago Segarra, Rice University and Zheng Zhang, Amazon AWS Shanghai AI lab and NYU Shanghai
 
 SS-L23.1: EFFICIENT BELIEF PROPAGATION FOR GRAPH MATCHING
         Efe Onaran; New York University
         Soledad Villar; New York University
 
 SS-L23.2: SUPERVISED GRAPH REPRESENTATION LEARNING FOR MODELING THE RELATIONSHIP BETWEEN STRUCTURAL AND FUNCTIONAL BRAIN CONNECTIVITY
         Yang Li; University of Rochester
         Rasoul Shafipour; University of Rochester
         Gonzalo Mateos; University of Rochester
         Zhengwu Zhang; University of Rochester
 
 SS-L23.3: STABILITY OF GRAPH NEURAL NETWORKS TO RELATIVE PERTURBATIONS
         Fernando Gama; University of Pennsylvania
         Joan Bruna; New York University
         Alejandro Ribeiro; University of Pennsylvania
 
 SS-L23.4: ACTIVE SEMI-SUPERVISED LEARNING FOR DIFFUSIONS ON GRAPHS
         Bishwadeep Das; Delft University of Technology
         Elvin Isufi; Delft University of Technology
         Geert Leus; Delft University of Technology
 
 SS-L23.5: STOCHASTIC GRAPH NEURAL NETWORKS
         Zhan Gao; University of Pennsylvania
         Elvin Isufi; Delft University of Technology
         Alejandro Ribeiro; University of Pennsylvania
 
 SS-L23.6: GENERATIVE ADVERSARIAL NETWORKS FOR GRAPH DATA IMPUTATION FROM SIGNED OBSERVATIONS
         Amarlingam Madapu; Indian Institute of Science
         Santiago Segarra; Rice University
         Sundeep Prabhakar Chepuri; Indian Institute of Science
         Antonio Marques; King Juan Carlos University