no code implementations • 10 Jan 2023 • Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Tirthankar Roy, Chonggang Xu, Binayak Mohanty, Kathryn Lawson
Here we present differentiable geoscientific modeling as a powerful pathway toward dissolving the perceived barrier between them and ushering in a paradigm shift.
no code implementations • 27 Nov 2021 • Luca Pion-Tonachini, Kristofer Bouchard, Hector Garcia Martin, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus Zwart, Neeraj Kumar, Amy Justice, Claire Tomlin, Daniel Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Ken Kreutz-Delgado, Michael W. Mahoney, James B. Brown
We outline emerging opportunities and challenges to enhance the utility of AI for scientific discovery.