Wavelet analysis is a new method called 'numerical microscope'in signal and image
processing. It has the desirable advantages of multi-resolution properties and various basis …

Recent progress in neural forecasting accelerated improvements in the performance of large-
scale forecasting systems. Yet, long-horizon forecasting remains a very difficult task. Two …

With massive advancements in sensor technologies and Internet-of-things (IoT), we now
have access to terabytes of historical data; however, there is a lack of clarity on how to best …

Remote sensing (RS) image retrieval is of great significant for geological information mining.
Over the past two decades, a large amount of research on this task has been carried out …

Estimating forest above‐ground biomass (AGB), or carbon (AGC), in tropical forests has
become a major concern for scientists and stakeholders. However, AGB assessment …

With massive advancements in sensor technologies and Internet-of-things, we now have
access to terabytes of historical data; however, there is a lack of clarity in how to best exploit …

This textbook has grown out of a course which we teach periodically at the University of
Iowa. We have beginning graduate students in mathematics who wish to work in numerical …

Deep neural operators are recognized as an effective tool for learning solution operators of
complex partial differential equations (PDEs). As compared to laborious analytical and …

In geotechnical engineering, the number of measurement data obtained from in situ or
laboratory tests is usually sparse, especially for projects of small or medium size …

Short-term water demand forecasting provides guidance on real-time water allocation in the
water supply network, which help water utilities reduce energy cost and avoid potential …