69 citations · 76 across the 4 of their papers we have counts for
4 papers
Deep Neural Network Learning with Second-Order Optimizers -- a Practical Study with a Stochastic Quasi-Gauss-Newton Method
Christopher Thiele, Mauricio Araya-Polo, Detlef Hohl
Training in supervised deep learning is computationally demanding, and the convergence behavior is usually not fully understood. We introduce and study a second-order stochastic qu…
Equation of state of fluid methane from first principles with machine learning potentials
Max Veit, Sandeep Kumar Jain, Satyanarayana Bonakala +3
The predictive simulation of molecular liquids requires models that are not only accurate, but computationally efficient enough to handle the large systems and long time scales req…
A data-driven workflow for predicting horizontal well production using vertical well logs
Jorge Guevara, Matthias Kormaksson, Bianca Zadrozny +6
In recent work, data-driven sweet spotting technique for shale plays previously explored with vertical wells has been proposed. Here, we extend this technique to multiple formation…
Performance Analysis and Optimization of a Hybrid Distributed Reverse Time Migration Application
Sri Raj Paul, John Mellor-Crummey, Mauricio Araya-Polo +1
Applications to process seismic data employ scalable parallel systems to produce timely results. To fully exploit emerging processor architectures, application will need to employ…