120 citations · 167 across the 7 of their papers we have counts for
8 papers
Experimental benchmarking of an automated deterministic error suppression workflow for quantum algorithms
Pranav S. Mundada, Aaron Barbosa, Smarak Maity +8
Excitement about the promise of quantum computers is tempered by the reality that the hardware remains exceptionally fragile and error-prone, forming a bottleneck in the developmen…
Automatic Infectious Disease Classification Analysis with Concept Discovery
Elena Sizikova, Joshua Vendrow, Xu Cao +13
Automatic infectious disease classification from images can facilitate needed medical diagnoses. Such an approach can identify diseases, like tuberculosis, which remain under-diagn…
Semi-supervised Nonnegative Matrix Factorization for Document Classification
Jamie Haddock, Lara Kassab, Sixian Li +9
We propose new semi-supervised nonnegative matrix factorization (SSNMF) models for document classification and provide motivation for these models as maximum likelihood estimators.…
Geometry of Linear Convolutional Networks
Kathlén Kohn, Thomas Merkh, Guido Montúfar +1
We study the family of functions that are represented by a linear convolutional neural network (LCN). These functions form a semi-algebraic subset of the set of linear maps from in…
Experimental Deep Reinforcement Learning for Error-Robust Gateset Design on a Superconducting Quantum Computer
Yuval Baum, Mirko Amico, Sean Howell +6
Quantum computers promise tremendous impact across applications -- and have shown great strides in hardware engineering -- but remain notoriously error prone. Careful design of low…
Semi-supervised NMF Models for Topic Modeling in Learning Tasks
Jamie Haddock, Lara Kassab, Sixian Li +9
We propose several new models for semi-supervised nonnegative matrix factorization (SSNMF) and provide motivation for SSNMF models as maximum likelihood estimators given specific d…