WE2.R7: Incorporating Physics into Deep Learning

Wed, 30 Sep, 14:30 - 16:30 (UTC)
Wed, 30 Sep, 22:30 - 00:30 China Standard Time (UTC +8)
Wed, 30 Sep, 16:30 - 18:30 Central Europe Summer Time (UTC +2)
Wed, 30 Sep, 07:30 - 09:30 Pacific Daylight Time (UTC -7)
Session Co-Chairs: Katarina Doctor, U.S. Naval Research Laboratory and Jocelyn Chanussot, Univ. Grenoble Alpes; University of Iceland
Session Managers: Ushasi Chaudhuri and Na Liu
Track: Invited Sessions
14:30-14:50 (UTC)
22:30-22:50 (UTC +8)
16:30-16:50 (UTC +2)
07:30-07:50 (UTC -7)

WE2.R7.1: Physics-guided Machine Learning: Advances in an Emerging Paradigm Combining Scientific Knowledge with Machine Learning

Anuj Karpatne, Virginia Tech, United States
14:50-15:00 (UTC)
22:50-23:00 (UTC +8)
16:50-17:00 (UTC +2)
07:50-08:00 (UTC -7)

WE2.R7.2: PHYSICALLY INFORMED NEURAL NETWORKS FOR THE SIMULATION AND DATA-ASSIMILATION OF GEOPHYSICAL DYNAMICS

Said Ouala, Ronan Fablet, Lucas Drumetz, IMT-Atlantique, France; Bertrand Chapron, Ifremer, France; Ananda Pascual, IMEDEA, Spain; Fabrice Collard, Lucile Gaultier, ODL, France
15:00-15:10 (UTC)
23:00-23:10 (UTC +8)
17:00-17:10 (UTC +2)
08:00-08:10 (UTC -7)

WE2.R7.3: PROCESS GUIDED DEEP LEARNING FOR MODELING PHYSICAL SYSTEMS: AN APPLICATION IN LAKE TEMPERATURE MODELING

Xiaowei Jia, Jared Willard, University of Minnesota, United States; Anuj Karpatne, Virginia Tech, United States; Jordan Read, Jacob Zwart, USGS, United States; Michael Steinbach, Vipin Kumar, University of Minnesota, United States
15:10-15:20 (UTC)
23:10-23:20 (UTC +8)
17:10-17:20 (UTC +2)
08:10-08:20 (UTC -7)

WE2.R7.4: VISUALIZATION OF DEEP TRANSFER LEARNING IN SAR IMAGERY

Abu Md Niamul Taufique, Navya Nagananda, Andreas Savakis, Rochester Institute of Technology, United States
15:20-15:30 (UTC)
23:20-23:30 (UTC +8)
17:20-17:30 (UTC +2)
08:20-08:30 (UTC -7)

WE2.R7.5: EXPLORING THE RELATIONSHIPS BETWEEN SCATTERING PHYSICS AND AUTO-ENCODER LATENT-SPACE EMBEDDING

Shaunak De, Christian Clanton, Steven Bickerton, Oliwia Baney, Kaushik Patnaik, Orbital Insight Inc., United States
15:30-15:40 (UTC)
23:30-23:40 (UTC +8)
17:30-17:40 (UTC +2)
08:30-08:40 (UTC -7)

WE2.R7.6: ON THE OPTIMAL DESIGN OF CONVOLUTIONAL NEURAL NETWORKS FOR EARTH OBSERVATION DATA ANALYSIS BY MAXIMIZATION OF INFORMATION EXTRACTION

Andrea Marinoni, UiT The Arctic University of Norway, Norway; Gianni Christian Iannelli, Ticinum Aerospace, Italy; Salman Khaleghian, UiT The Arctic University of Norway, Norway; Paolo Gamba, University of Pavia, Italy
15:40-15:50 (UTC)
23:40-23:50 (UTC +8)
17:40-17:50 (UTC +2)
08:40-08:50 (UTC -7)

WE2.R7.7: BUILDING EXTRACTION BY GATED GRAPH CONVOLUTIONAL NEURAL NETWORK WITH DEEP STRUCTURED FEATURE EMBEDDING

Yilei Shi, Qinyu Li, Xiao Xiang Zhu, Technical University of Munich, Germany
15:50-16:00 (UTC)
23:50-00:00 (UTC +8)
17:50-18:00 (UTC +2)
08:50-09:00 (UTC -7)

WE2.R7.8: MULTI-SPECTRAL IMAGE CLASSIFICATION WITH QUANTUM NEURAL NETWORK

Piotr Gawron, Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Poland; Stanisław Lewiński, Space Research Centre, Polish Academy of Sciences, Poland
16:00-16:10 (UTC)
00:00-00:10 (UTC +8)
18:00-18:10 (UTC +2)
09:00-09:10 (UTC -7)

WE2.R7.9: AN ENSEMBLE APPROACH FOR COMPRESSIVE SENSING WITH QUANTUM ANNEALERS

Ramin Ayanzadeh, Milton Halem, Tim Finin, University of Maryland, Baltimore County, United States