Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
– Efficient implementations of the Discrete Fourier Transform (DFT) for GPUs provide good performance with large data sizes, but are not competitive with CPU code for small data ...
Parallel processors such as SIMD computers have been successfully used in various areas of high performance image and data processing. Due to their characteristics of highly regula...
We address the problem of data parallel processing for computational quantum chemistry (CQC). CQC is a computationally demanding tool to study the electronic structure of molecule...
Tirath Ramdas, Gregory K. Egan, David Abramson, Ki...