17 citations · 17 across the 1 of their papers we have counts for
3 papers
Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling
Pu Ren, Rie Nakata, Maxime Lacour +9
Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer fro…
Efficient Leverage Score Sampling for Tensor Train Decomposition
Vivek Bharadwaj, Beheshteh T. Rakhshan, Osman Asif Malik +1
Tensor Train~(TT) decomposition is widely used in the machine learning and quantum physics communities as a popular tool to efficiently compress high-dimensional tensor data. In th…
Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software
Riley Murray, James Demmel, Michael W. Mahoney +10
Randomized numerical linear algebra - RandNLA, for short - concerns the use of randomization as a resource to develop improved algorithms for large-scale linear algebra computation…