WQ-L.A: Machine Learning for Computational Imaging in Earth Sciences
Wed, 19 Oct, 20:00 - 22:00 China Standard Time (UTC +8)
Wed, 19 Oct, 14:00 - 16:00 Central European Time (UTC +2)
Wed, 19 Oct, 12:00 - 14:00 UTC
Wed, 19 Oct, 08:00 - 10:00 Eastern Time (UTC -4)
Lecture
Special Session
Location: Room A
Session Chair: Amir Adler, Braude College of Engineering & Massachusetts Institute of Technology
Track: Special Sessions

WQ-L.A.1: 3D GEOMETRY DESIGN VIA END-TO-END OPTIMIZATION FOR LAND SEISMIC ACQUISITION
Alejandra Hernandez-Rojas, Henry Arguello, Universidad Industrial de Santander, Colombia

WQ-L.A.2: PROBING SEISMOGENIC FAULTS WITH MACHINE LEARNING
Paul Johnson, Chris Johnson, Los Alamos National Laboratory, United States of America

WQ-L.A.3: EARTHQUAKE LOCATION AND MAGNITUDE ESTIMATION WITH GRAPH NEURAL NETWORKS
Ian McBrearty, Gregory Beroza, Stanford University, United States of America

WQ-L.A.4: DIRECT IMAGING USING PHYSICS INFORMED NEURAL NETWORKS
Tariq Alkhalifah, Xinquan Huang, King Abdullah University for Science and Technology (KAUST), Saudi Arabia

WQ-L.A.5: SRL-SOA: SELF-REPRESENTATION LEARNING WITH SPARSE 1D-OPERATIONAL AUTOENCODER FOR HYPERSPECTRAL IMAGE BAND SELECTION
Mete Ahishali, Moncef Gabbouj, Tampere University, Finland; Serkan Kiranyaz, Qatar University, Qatar; Iftikhar Ahmad, Tietoevry, Finland

WQ-L.A.6: Semi-supervised Deep Convolutional Transform Learning for Hyperspectral Image Classification
Shikha Singh, IIIT Delhi, India; Angshul Majumdar, Indraprastha Institute of Information Technology, India; Emilie Chouzenoux, Inria, France; Giovanni Chierchia, ESIEE, France