Computation, Optimization, and Machine Learning in Seismology\n\nSubhashis Mallick (Author)\n\n9781119654469, Wiley\n\nPaperback / softback, published 2 October 2025\n\n416 pages\n24.9 x 17.5 x 2 cm, 0.771 kg\n\nA textbook applying fundamental seismology theories to the latest computational tools \nThe goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances in computing technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models. \nComputation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data. \nVolume highlights include:\n--Mathematical foundations and key equations for computational seismol]