SPTM-18.2
SEISMIC FAULT IDENTIFICATION USING GRAPH HIGH-FREQUENCY COMPONENTS AS INPUT TO GRAPH CONVOLUTIONAL NETWORK
Patitapaban Palo, Aurobinda Routray, IIT Kharagpur, India
Session:
Adaptation and Learning Over Graphs
Track:
Signal Processing Theory and Methods
Location:
Gather Area M
Presentation Time:
Thu, 12 May, 21:00 - 21:45 China Time (UTC +8)
Thu, 12 May, 13:00 - 13:45 UTC
Thu, 12 May, 13:00 - 13:45 UTC
Session Chair:
Stefan Vlaski, Imperial College London
Session SPTM-18
SPTM-18.1: OPTIMAL COMBINATION POLICIES FOR ADAPTIVE SOCIAL LEARNING
Ping Hu, Virginia Bordignon, Ali H. Sayed, EPFL, Switzerland; Stefan Vlaski, Imperial College London, United Kingdom of Great Britain and Northern Ireland
SPTM-18.2: SEISMIC FAULT IDENTIFICATION USING GRAPH HIGH-FREQUENCY COMPONENTS AS INPUT TO GRAPH CONVOLUTIONAL NETWORK
Patitapaban Palo, Aurobinda Routray, IIT Kharagpur, India
SPTM-18.3: DISTRIBUTED GRAPH LEARNING WITH SMOOTH DATA PRIORS
Isabela Cunha Maia Nobre, Pascal Frossard, EPFL, Switzerland; Mireille El Gheche, Sony AI, Switzerland
SPTM-18.4: ADVERSPARSE: AN ADVERSARIAL ATTACK FRAMEWORK FOR DEEP SPATIAL-TEMPORAL GRAPH NEURAL NETWORKS
Jiayu Li, Shengmin Jin, Makan Fardad, Reza Zafarani, Syracuse University, United States of America; Tianyun Zhang, Cleveland State University, United States of America
SPTM-18.5: MULTIMODAL GRAPH SIGNAL DENOISING VIA TWOFOLD GRAPH SMOOTHNESS REGULARIZATION WITH DEEP ALGORITHM UNROLLING
Masatoshi Nagahama, Yuichi Tanaka, Tokyo University of Agriculture and Technology, Japan
SPTM-18.6: Heterogeneous Graph Node Classification with Multi-Hops Relation Features
Xiaolong Xu, Lingjuan Lyu, Hong Jin, Weiqiang Wang, Shuo Jia, ANT GROUP, China