research
∙
03/16/2023
Challenges and Opportunities in Quantum Machine Learning
At the intersection of machine learning and quantum computing, Quantum M...
share
research
∙
11/09/2022
Resource frugal optimizer for quantum machine learning
Quantum-enhanced data science, also known as quantum machine learning (Q...
research
∙
06/30/2022
Practical Black Box Hamiltonian Learning
We study the problem of learning the parameters for the Hamiltonian of a...
research
∙
04/21/2022
Dynamical simulation via quantum machine learning with provable generalization
Much attention has been paid to dynamical simulation and quantum machine...
research
∙
04/21/2022
Out-of-distribution generalization for learning quantum dynamics
Generalization bounds are a critical tool to assess the training data re...
research
∙
04/07/2022
Covariance matrix preparation for quantum principal component analysis
Principal component analysis (PCA) is a dimensionality reduction method ...
research
∙
11/09/2021
Generalization in quantum machine learning from few training data
Modern quantum machine learning (QML) methods involve variationally opti...
research
∙
09/02/2021
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?
Variational Quantum Algorithms (VQAs) are widely viewed as the best hope...
research
∙
03/11/2021
A semi-agnostic ansatz with variable structure for quantum machine learning
Quantum machine learning (QML) offers a powerful, flexible paradigm for ...
research
∙
02/10/2021
Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers
Combinatorial optimization on near-term quantum devices is a promising p...
research
∙
02/08/2021
Long-time simulations with high fidelity on quantum hardware
Moderate-size quantum computers are now publicly accessible over the clo...
research
∙
12/16/2020
Variational Quantum Algorithms
Applications such as simulating large quantum systems or solving large-s...
research
∙
11/24/2020
Effect of barren plateaus on gradient-free optimization
Barren plateau landscapes correspond to gradients that vanish exponentia...
research
∙
07/28/2020
Noise-Induced Barren Plateaus in Variational Quantum Algorithms
Variational Quantum Algorithms (VQAs) may be a path to quantum advantage...
research
∙
07/09/2020
Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets
The No-Free-Lunch (NFL) theorem is a celebrated result in learning theor...
research
∙
05/26/2020
Trainability of Dissipative Perceptron-Based Quantum Neural Networks
Several architectures have been proposed for quantum neural networks (QN...
research
∙
01/02/2020
Cost-Function-Dependent Barren Plateaus in Shallow Quantum Neural Networks
Variational quantum algorithms (VQAs) optimize the parameters θ of a qua...
research
∙
11/25/2019
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems
Quantum computing is a computational paradigm with the potential to outp...
research
∙
11/11/2019