Media Summary: Authors: Sacha Lerch, Ricard Puig, Manuel Rudolph, Armando Angrisani, Tyson Jones, Supanut Thanasilp, Marco Cerezo and ... Authors: Marco Ballarin, Juan José García-Ripoll, David Hayes and Michael Lubasch Abstract: Speaker: Kouhei Nakaji Abstract: The convergence of artificial intelligence (AI) and

Qtml 2025 Efficient Quantum Enhanced - Detailed Analysis & Overview

Authors: Sacha Lerch, Ricard Puig, Manuel Rudolph, Armando Angrisani, Tyson Jones, Supanut Thanasilp, Marco Cerezo and ... Authors: Marco Ballarin, Juan José García-Ripoll, David Hayes and Michael Lubasch Abstract: Speaker: Kouhei Nakaji Abstract: The convergence of artificial intelligence (AI) and Authors: Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert, Elies Gil-Fuster, Franz J. Schreiber and Carlos Bravo-Prieto ... Speaker: Sofiene Jerbi Abstract: In this talk, I will present two recent works related to the question of Speaker: Joseph Bowles Abstract: I will show how Fourier analysis can be used to construct

Authors: Nicholas Rubin, Guanghao Low, Robbie King, Eugene DePrince, Alec White, Ryan Babbush, Dominic Berry and ... Authors: Adrián Pérez-Salinas, Patrick Emonts, Jordi Tura Brugués and Vedran Dunjko Abstract: Classical simulation of Authors: Aiden Rosebush, Alexander Greenwood and Li Qian Abstract: We propose a machine learning based approach to ... Authors: Nana Liu, Michele Minverini, Dhrumil Patel and Mark Wilde Abstract: In Speaker: Seth Lloyd Abstract: When a physical system gets information from the outside world, processes that information, and ... Authors: Zihao Li, Changhao Yi, You Zhou and Huangjun Zhu Abstract: Classical shadow estimation (CSE) is a powerful tool for ...

Authors: Xiufan Li, Soumik Adhikary and Patrick Rebentrost Abstract:

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QTML 2025: Efficient quantum-enhanced classical simulation for patches of quantum landscapes
QTML 2025: Efficient quantum state preparation of multivariate functions using tensor networks
QTML 2025: AI for Quantum: Toward AI-Enhanced Quantum Computing Applications
QTML 2025: A PAC-Bayesian Approach To Generalization For Quantum models
QTML 2025: Shadows of quantum machine learning and shallow-depth learning separations
QTML 2025: Scalable quantum machine learning models in Fourier space
QTML 2025:  Quantum Simulation By Sum Of Squares Spectral Amplification
QTML 2025: Multiple-Basis Representation Of Quantum States
QTML 2025: A Universal Script for Machine Learning Derived Entanglement Witnesses
QTML 2025: Quantum thermodynamics and semi-definite optimization
QTML 2025: Quantum world models for a quantum world
QTML 2025: Nearly query-optimal classical shadow estimation of unitary channels
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QTML 2025: Efficient quantum-enhanced classical simulation for patches of quantum landscapes

QTML 2025: Efficient quantum-enhanced classical simulation for patches of quantum landscapes

Authors: Sacha Lerch, Ricard Puig, Manuel Rudolph, Armando Angrisani, Tyson Jones, Supanut Thanasilp, Marco Cerezo and ...

QTML 2025: Efficient quantum state preparation of multivariate functions using tensor networks

QTML 2025: Efficient quantum state preparation of multivariate functions using tensor networks

Authors: Marco Ballarin, Juan José García-Ripoll, David Hayes and Michael Lubasch Abstract:

QTML 2025: AI for Quantum: Toward AI-Enhanced Quantum Computing Applications

QTML 2025: AI for Quantum: Toward AI-Enhanced Quantum Computing Applications

Speaker: Kouhei Nakaji Abstract: The convergence of artificial intelligence (AI) and

QTML 2025: A PAC-Bayesian Approach To Generalization For Quantum models

QTML 2025: A PAC-Bayesian Approach To Generalization For Quantum models

Authors: Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert, Elies Gil-Fuster, Franz J. Schreiber and Carlos Bravo-Prieto ...

QTML 2025: Shadows of quantum machine learning and shallow-depth learning separations

QTML 2025: Shadows of quantum machine learning and shallow-depth learning separations

Speaker: Sofiene Jerbi Abstract: In this talk, I will present two recent works related to the question of

QTML 2025: Scalable quantum machine learning models in Fourier space

QTML 2025: Scalable quantum machine learning models in Fourier space

Speaker: Joseph Bowles Abstract: I will show how Fourier analysis can be used to construct

QTML 2025:  Quantum Simulation By Sum Of Squares Spectral Amplification

QTML 2025: Quantum Simulation By Sum Of Squares Spectral Amplification

Authors: Nicholas Rubin, Guanghao Low, Robbie King, Eugene DePrince, Alec White, Ryan Babbush, Dominic Berry and ...

QTML 2025: Multiple-Basis Representation Of Quantum States

QTML 2025: Multiple-Basis Representation Of Quantum States

Authors: Adrián Pérez-Salinas, Patrick Emonts, Jordi Tura Brugués and Vedran Dunjko Abstract: Classical simulation of

QTML 2025: A Universal Script for Machine Learning Derived Entanglement Witnesses

QTML 2025: A Universal Script for Machine Learning Derived Entanglement Witnesses

Authors: Aiden Rosebush, Alexander Greenwood and Li Qian Abstract: We propose a machine learning based approach to ...

QTML 2025: Quantum thermodynamics and semi-definite optimization

QTML 2025: Quantum thermodynamics and semi-definite optimization

Authors: Nana Liu, Michele Minverini, Dhrumil Patel and Mark Wilde Abstract: In

QTML 2025: Quantum world models for a quantum world

QTML 2025: Quantum world models for a quantum world

Speaker: Seth Lloyd Abstract: When a physical system gets information from the outside world, processes that information, and ...

QTML 2025: Nearly query-optimal classical shadow estimation of unitary channels

QTML 2025: Nearly query-optimal classical shadow estimation of unitary channels

Authors: Zihao Li, Changhao Yi, You Zhou and Huangjun Zhu Abstract: Classical shadow estimation (CSE) is a powerful tool for ...

QTML 2025:  StoCQS: Stochastic Strategy For Ansatz Tree Construction In Krylov-Based Linear Solver

QTML 2025: StoCQS: Stochastic Strategy For Ansatz Tree Construction In Krylov-Based Linear Solver

Authors: Xiufan Li, Soumik Adhikary and Patrick Rebentrost Abstract: