47 citations · 78 across the 15 of their papers we have counts for
15 papers
On the Dynamics of Learning Time-Aware Behavior with Recurrent Neural Networks
Peter DelMastro, Rushiv Arora, Edward Rietman +1
Recurrent Neural Networks (RNNs) have shown great success in modeling time-dependent patterns, but there is limited research on their learned representations of latent temporal fea…
Signal Propagation: A Framework for Learning and Inference In a Forward Pass
Adam Kohan, Edward A. Rietman, Hava T. Siegelmann
We propose a new learning framework, signal propagation (sigprop), for propagating a learning signal and updating neural network parameters via a forward pass, as an alternative to…
Content Addressable Parallel Processors on a FPGA
Ayush Salik, Manor Askenazi, Edward Rietman
In this short article, we report on the implementation of a Content Addressable Parallel Processor using a FPGA. While Content addressable memories have been implemented in FPGAs,…
Acoustic Bandgaps of Phononic Penrose and Quasicrystals
Bryan Eastwood, Edward A. Rietman
Using 3D printing we manufactured two rodlike phononic crystals. Viewed from the top, one is a Penrose tile and the second is a quasicrystal. We explored the acoustic properties an…
Deep Learning Regression of VLSI Plasma Etch Metrology
Jack Kenney, John Valcore, Scott Riggs +1
In computer chip manufacturing, the study of etch patterns on silicon wafers, or metrology, occurs on the nano-scale and is therefore subject to large variation from small, yet sig…
Unsupervised Machine Learning to Teach Fluid Dynamicists to Think in 15 Dimensions
S. M. de Bruyn Kops, D. J. Saunders, E. A. Rietman +1
An autoencoder is used to compress and then reconstruct three-dimensional stratified turbulence data in order to better understand fluid dynamics by studying the errors in the reco…