3 citations · 3 across the 3 of their papers we have counts for
4 papers
In Situ Training of Implicit Neural Compressors for Scientific Simulations via Sketch-Based Regularization
Cooper Simpson, Stephen Becker, Alireza Doostan
Focusing on implicit neural representations, we present a novel in situ training protocol that employs limited memory buffers of full and sketched data samples, where the sketched…
In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD
Riccardo Balin, Filippo Simini, Cooper Simpson +7
Recent years have seen many successful applications of machine learning (ML) to facilitate fluid dynamic computations. As simulations grow, generating new training datasets for tra…
QuadConv: Quadrature-Based Convolutions with Applications to Non-Uniform PDE Data Compression
Kevin Doherty, Cooper Simpson, Stephen Becker +1
We present a new convolution layer for deep learning architectures which we call QuadConv -- an approximation to continuous convolution via quadrature. Our operator is developed ex…
Embedded Neural Networks for Robot Autonomy
Sarah Aguasvivas Manzano, Dana Hughes, Cooper Simpson +2
We present a library to automatically embed signal processing and neural network predictions into the material robots are made of. Deep and shallow neural network models are first…