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09/29/2022
Joint Embedding Self-Supervised Learning in the Kernel Regime
The fundamental goal of self-supervised learning (SSL) is to produce use...
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08/12/2022
Wasserstein Complexity of Quantum Circuits
Given a unitary transformation, what is the size of the smallest quantum...
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03/10/2022
projUNN: efficient method for training deep networks with unitary matrices
In learning with recurrent or very deep feed-forward networks, employing...
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01/27/2022
Quantum algorithm for dense kernel matrices using hierarchical splitting
Kernel matrices, which arise from discretizing a kernel function k(x,x')...
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09/23/2021
Quantum algorithms for group convolution, cross-correlation, and equivariant transformations
Group convolutions and cross-correlations, which are equivariant to the ...
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07/19/2021
A quantum algorithm for training wide and deep classical neural networks
Given the success of deep learning in classical machine learning, quantu...
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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...
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10/29/2020
Quantum advantage for differential equation analysis
Quantum algorithms for both differential equation solving and for machin...
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09/09/2020
The quantum Wasserstein distance of order 1
We propose a generalization of the Wasserstein distance of order 1 to th...
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06/30/2020
Quantum algorithm for Petz recovery channels and pretty good measurements
The Petz recovery channel plays an important role in quantum information...
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04/13/2020
Adversarial robustness guarantees for random deep neural networks
The reliability of most deep learning algorithms is fundamentally challe...
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04/04/2020
Quantum Medical Imaging Algorithms
A central task in medical imaging is the reconstruction of an image or f...
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01/31/2020
Learning Unitaries by Gradient Descent
We study the hardness of learning unitary transformations by performing ...
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11/05/2019
Thermodynamic Computing
The hardware and software foundations laid in the first half of the 20th...
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05/24/2019
Quantum-inspired algorithms in practice
We study the practical performance of quantum-inspired algorithms for re...
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12/25/2018
Deep neural networks are biased towards simple functions
We prove that the binary classifiers of bit strings generated by random ...
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11/12/2018
Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension
We construct an efficient classical analogue of the quantum matrix inver...
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06/18/2018