Scientific Machine Learning for Dynamical Systems: Theory and Applications to Fluid Flow and Ocean Ecosystem Modeling by Gupta, Abhinav

“…It employs Dynamically Orthogonal (DO) differential equations for adaptive reduced-order stochastic evolution, and the Gaussian Mixture Model-DO (GMM-DO) filter for simultaneous nonlinear inference in the augmented space of state variables, parameters, and model equations. …”
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Methane emissions in the United States, Canada, and Mexico: evaluation of national methane emission inventories and 2010–2017 sectoral trends by inverse analysis of in situ (GLOBAL... by X. Lu, X. Lu, X. Lu, D. J. Jacob, H. Wang, J. D. Maasakkers, Y. Zhang, Y. Zhang, Y. Zhang, T. R. Scarpelli, L. Shen, Z. Qu, M. P. Sulprizio, H. Nesser, A. A. Bloom, S. Ma, J. R. Worden, S. Fan, R. J. Parker, R. J. Parker, H. Boesch, H. Boesch, R. Gautam, D. Gordon, D. Gordon, M. D. Moran, F. Reuland, C. A. O. Villasana, A. Andrews

“…Emissions are optimized with a Gaussian mixture model (GMM) at <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">0.5</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">0.625</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="64pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="a5e38fd50863438f548f267f2cc9a123"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-395-2022-ie00001.svg" width="64pt" height="11pt" src="acp-22-395-2022-ie00001.png"/></svg:svg></span></span> resolution and for individual years. …”
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