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- Title: Deep learning for hurricane forecastingAbstract: The forecast of hurricane trajectories is crucial for the protection of people and property, but machine learning techniques have been scarce for this so far. I will present a method that
- Title: "Efficient representation of high-order finite element operators"Abstract: We present an extensible low-level library that provides a versatile algebraic interface and optimized implementations suitable for high-order operators: libCEED
- Private AI (or: How to Keep Your Location Data Secret)As the world rushes towards the adoption of Artificial Intelligence (AI) in all aspects of our lives, the promise is great, but the risks are many. AI can help to improve and simplify our daily
- Title: "Approximation of parametrized kernels arising in nonlocal and fractional Laplace models"Abstract: We consider parametrized linear and obstacle problems driven by a spatially nonlocal integral operator. These problems have a broad
- In many applications throughout science and engineering, model reduction plays an important role replacing expensive large-scale linear dynamical systems by inexpensive reduced order models that capture key features of the original, full order model
- Spatiotemporal Dynamics of Neocortical Seizure ActivitySeizures are defined as sudden, abnormal electrical disturbances in the brain. Patients diagnosed with epilepsy have chronic, recurrent seizures and often require clinical intervention to
- Spacecraft Mission DesignNewton’s laws are used to design spacecraft missions to explore our solar system. Onboard controls are used to change the velocity and orientation of a spacecraft. Mission design must combine dynamics, control theory, and
- Introduction to the Institute for Telecommunication Sciences (ITS)The Institute for Telecommunication Sciences (ITS) is the research and engineering laboratory for the National Telecommunications and Information Administration (NTIA). The NTIA
- Beyond sparsity: compressed sensing with deep generative priors Over the last several decades, sparsity and compressed sensing has been a dominant theme in signal recovery, leading to significant improvements in MRI imaging and new algorithms in a
- Data Science Meets GeometryEvery minute, the humankind produces about 2000 Terabytes of data and learning from this data has the potential to improve many aspects of our lives. Doing so requires exploiting the geometric structure hidden within the