Title: Quantum Convolutional Neural Networks are (Effectively) Classically Simulable Abstract: Quantum Convolutional Neural Networks (QCNNs) are widely regarded as a promising model for Quantum Machine Learning (QML). In this work […]

Title: Classical shadows in theory, numerics and experiment Abstract: Classical shadows are a scalable way to extract meaningful information from a n-qubit system in a scalable and online fashion. Crucially, […]

Title: Reservoir computing with complex quantum systems Abstract: Non-conventional computing inspired by the brain, or neuromorphic computing, is a successful approach in a broad spectrum of applications, and in the […]

Title: But why would we use quantum computers after all? Approaching Quantum Machine Learning a little differently Abstract: The last years of research in quantum machine learning have taught us […]

he 9th edition of the Quantum Information in Spain (ICE) conference will be held from the 11th to the 15th of November 2024 at Puerto de la Cruz (Tenerife). ICE is […]

Speaker: Marco Cerezo Title: Is Quantum Machine Learning an ill-defined framework? Abstract: In this talk we will discuss some our recent results regarding the trainability and classical simulability of Quantum […]

Speaker: Diego Andrade Canosa Abstract: Benchmarking Quantum Computers is required to objectively evaluate these platforms' performance, stressing their capabilities and leading the evolution of the hardware platforms. Some approaches work at […]

Speaker: Vedran Dunjko Title: Topics in quantum topological data analysis Abstract: Although still arguably an emerging field in classical machine learning, topological data analysis has already raised substantial interest from the perspective of quantum algorithms […]

The workshop consists of 3 Friday afternoon sessions on February 28, February 7 and March 14, 2025 from 15-19 hrs, and a full day Hackathon on Firday March 21, 2025. […]