Search Results for author: Davide Ferrari

Found 6 papers, 0 papers with code

Multi-Class Quantum Convolutional Neural Networks

no code implementations19 Apr 2024 Marco Mordacci, Davide Ferrari, Michele Amoretti

The results show that with 4 classes, the performance is slightly lower compared to the classical CNN, while with a higher number of classes, the QCNN outperforms the classical neural network.

Information Retrieval Multi-class Classification +1

Question answering systems for health professionals at the point of care -- a systematic review

no code implementations24 Jan 2024 Gregory Kell, Angus Roberts, Serge Umansky, Linglong Qian, Davide Ferrari, Frank Soboczenski, Byron Wallace, Nikhil Patel, Iain J Marshall

Results: We included 79 studies and identified themes, including question realism, answer reliability, answer utility, clinical specialism, systems, usability, and evaluation methods.

Question Answering

Safe Multimodal Communication in Human-Robot Collaboration

no code implementations7 Aug 2023 Davide Ferrari, Andrea Pupa, Alberto Signoretti, Cristian Secchi

The new industrial settings are characterized by the presence of human and robots that work in close proximity, cooperating in performing the required job.

Deterministic Algorithms for Compiling Quantum Circuits with Recurrent Patterns

no code implementations17 Feb 2021 Davide Ferrari, Ivano Tavernelli, Michele Amoretti

In particular, such patterns appear in quantum circuits that are used to compute the ground state properties of molecular systems using the variational quantum eigensolver (VQE) method together with the RyRz heuristic wavefunction Ansatz.

Quantum Physics Computational Complexity Data Structures and Algorithms

Compiler Design for Distributed Quantum Computing

no code implementations17 Dec 2020 Davide Ferrari, Angela Sara Cacciapuoti, Michele Amoretti, Marcello Caleffi

In distributed quantum computing architectures, with the network and communications functionalities provided by the Quantum Internet, remote quantum processing units (QPUs) can communicate and cooperate for executing computational tasks that single NISQ devices cannot handle by themselves.

Quantum Physics Distributed, Parallel, and Cluster Computing Networking and Internet Architecture

Efficient and Effective Quantum Compiling for Entanglement-based Machine Learning on IBM Q Devices

no code implementations8 Jan 2018 Davide Ferrari, Michele Amoretti

Quantum compiling means fast, device-aware implementation of quantum algorithms (i. e., quantum circuits, in the quantum circuit model of computation).

BIG-bench Machine Learning Quantum Machine Learning

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