research
∙
09/23/2021
Quantum algorithms for group convolution, cross-correlation, and equivariant transformations
Group convolutions and cross-correlations, which are equivariant to the ...
share
research
∙
01/08/2021
Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data
Quantifying how far the output of a learning algorithm is from its targe...
research
∙
10/29/2020
Quantum advantage for differential equation analysis
Quantum algorithms for both differential equation solving and for machin...
research
∙
09/09/2020
The quantum Wasserstein distance of order 1
We propose a generalization of the Wasserstein distance of order 1 to th...
research
∙
04/13/2020
Adversarial robustness guarantees for random deep neural networks
The reliability of most deep learning algorithms is fundamentally challe...
research
∙
12/25/2018
Deep neural networks are biased towards simple functions
We prove that the binary classifiers of bit strings generated by random ...
research
∙
08/24/2018
The Entropy Power Inequality with quantum conditioning
The conditional Entropy Power Inequality is a fundamental inequality in ...
research
∙
05/31/2018
New lower bounds to the output entropy of multi-mode quantum Gaussian channels
We prove that quantum thermal Gaussian input states minimize the output ...
research
∙
03/06/2018
Gaussian optimizers for entropic inequalities in quantum information
We survey the state of the art for the proof of the quantum Gaussian opt...
research
∙
03/01/2018