Patrick Rebentrost

According to our database, Patrick Rebentrost authored at least 23 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A quantum online portfolio optimization algorithm.

Debbie Lim, Patrick Rebentrost

Quantum Inf. Process., March, 2024

Low depth amplitude estimation without really trying.

Dinh-Long Vu, Bin Cheng, Patrick Rebentrost

CoRR, 2024

Concept learning of parameterized quantum models from limited measurements.

Beng Yee Gan, Po-Wei Huang, Elies Gil-Fuster, Patrick Rebentrost

CoRR, 2024

Quantum algorithm for large-scale market equilibrium computation.

Po-Wei Huang, Patrick Rebentrost

CoRR, 2024

Efficient Quantum Circuits for Machine Learning Activation Functions including Constant T-depth ReLU.

Wei Zi, Siyi Wang, Hyunji Kim, Xiaoming Sun, Anupam Chattopadhyay, Patrick Rebentrost

CoRR, 2024

Quantum linear algebra is all you need for Transformer architectures.

Naixu Guo, Zhan Yu, Aman Agrawal, Patrick Rebentrost

CoRR, 2024

2023

Quantum Alphatron: quantum advantage for learning with kernels and noise.

Siyi Yang, Naixu Guo, Miklos Santha, Patrick Rebentrost

Quantum, November, 2023

Quantum Algorithms for the Pathwise Lasso.

João F. Doriguello, Debbie Lim, Chi Seng Pun, Patrick Rebentrost, Tushar Vaidya

CoRR, 2023

Learning Restricted Boltzmann Machines with greedy quantum search.

Liming Zhao, Aman Agrawal, Patrick Rebentrost

CoRR, 2023

Hybrid quantum-classical and quantum-inspired classical algorithms for solving banded circulant linear systems.

Po-Wei Huang, Xiufan Li, Kelvin Koor, Patrick Rebentrost

CoRR, 2023

Provable learning of quantum states with graphical models.

Liming Zhao, Naixu Guo, Ming-Xing Luo, Patrick Rebentrost

CoRR, 2023

Post-variational quantum neural networks.

Po-Wei Huang, Patrick Rebentrost

CoRR, 2023

2022

Quantum Algorithm for Stochastic Optimal Stopping Problems with Applications in Finance.

João F. Doriguello, Alessandro Luongo, Jinge Bao, Patrick Rebentrost, Miklos Santha

Proceedings of the 17th Conference on the Theory of Quantum Computation, 2022

2021

Compiling basic linear algebra subroutines for quantum computers.

Liming Zhao, Zhikuan Zhao, Patrick Rebentrost, Joseph F. Fitzsimons

Quantum Mach. Intell., 2021

Smooth input preparation for quantum and quantum-inspired machine learning.

Zhikuan Zhao, Jack K. Fitzsimons, Patrick Rebentrost, Vedran Dunjko, Joseph F. Fitzsimons

Quantum Mach. Intell., 2021

Quantum algorithm for structure learning of Markov Random Fields.

Liming Zhao, Siyi Yang, Patrick Rebentrost

CoRR, 2021

2020

Robust quantum minimum finding with an application to hypothesis selection.

Yihui Quek, Clément L. Canonne, Patrick Rebentrost

CoRR, 2020

2019

Bayesian deep learning on a quantum computer.

Zhikuan Zhao, Alejandro Pozas-Kerstjens, Patrick Rebentrost, Peter Wittek

Quantum Mach. Intell., 2019

Batched quantum state exponentiation and quantum Hebbian learning.

Thomas R. Bromley, Patrick Rebentrost

Quantum Mach. Intell., 2019

Quantum and classical algorithms for approximate submodular function minimization.

Yassine Hamoudi, Patrick Rebentrost, Ansis Rosmanis, Miklos Santha

Quantum Inf. Comput., 2019

Near-term quantum algorithms for linear systems of equations.

Hsin-Yuan Huang, Kishor Bharti, Patrick Rebentrost

CoRR, 2019

2017

Quantum machine learning.

Jacob D. Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, Seth Lloyd

Nat., 2017

2013

Quantum support vector machine for big feature and big data classification.

Patrick Rebentrost, Masoud Mohseni, Seth Lloyd

CoRR, 2013