Lorenzo Buffoni

According to our database, Lorenzo Buffoni authored at least 23 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Stable attractors for neural networks classification via ordinary differential equations (SA-nODE).

Raffaele Marino, Lorenzo Buffoni, Lorenzo Chicchi, Lorenzo Giambagli, Duccio Fanelli

Mach. Learn. Sci. Technol., 2024

Deterministic versus stochastic dynamical classifiers: opposing random adversarial attacks with noise.

Lorenzo Chicchi, Duccio Fanelli, Diego Febbe, Lorenzo Buffoni, Francesca Di Patti, Lorenzo Giambagli, Raffaele Marino

CoRR, 2024

Learning in Wilson-Cowan model for metapopulation.

Raffaele Marino, Lorenzo Buffoni, Lorenzo Chicchi, Francesca Di Patti, Diego Febbe, Lorenzo Giambagli, Duccio Fanelli

CoRR, 2024

Automatic Input Feature Relevance via Spectral Neural Networks.

Lorenzo Chicchi, Lorenzo Buffoni, Diego Febbe, Lorenzo Giambagli, Raffaele Marino, Duccio Fanelli

CoRR, 2024

A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms.

Raffaele Marino, Lorenzo Buffoni, Bogdán Zaválnij

CoRR, 2024

2023

Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network.

Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp

Nat. Mac. Intell., October, 2023

Quantum density peak clustering.

Duarte Magano, Lorenzo Buffoni, Yasser Omar

Quantum Mach. Intell., June, 2023

Cooperative quantum information erasure.

Lorenzo Buffoni, Michele Campisi

Quantum, March, 2023

Complex Recurrent Spectral Network.

Lorenzo Chicchi, Lorenzo Giambagli, Lorenzo Buffoni, Raffaele Marino, Duccio Fanelli

CoRR, 2023

A Bridge between Dynamical Systems and Machine Learning: Engineered Ordinary Differential Equations as Classification Algorithm (EODECA).

Raffaele Marino, Lorenzo Giambagli, Lorenzo Chicchi, Lorenzo Buffoni, Duccio Fanelli

CoRR, 2023

How a Student becomes a Teacher: learning and forgetting through Spectral methods.

Lorenzo Giambagli, Lorenzo Buffoni, Lorenzo Chicchi, Duccio Fanelli

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Noise fingerprints in quantum computers: Machine learning software tools.

Stefano Martina, Stefano Gherardini, Lorenzo Buffoni, Filippo Caruso

Softw. Impacts, 2022

Quantum reinforcement learning: the maze problem.

Nicola Dalla Pozza, Lorenzo Buffoni, Stefano Martina, Filippo Caruso

Quantum Mach. Intell., 2022

Learning the noise fingerprint of quantum devices.

Stefano Martina, Lorenzo Buffoni, Stefano Gherardini, Filippo Caruso

Quantum Mach. Intell., 2022

Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network.

Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp

CoRR, 2022

Recurrent Spectral Network (RSN): shaping the basin of attraction of a discrete map to reach automated classification.

Lorenzo Chicchi, Duccio Fanelli, Lorenzo Giambagli, Lorenzo Buffoni, Timoteo Carletti

CoRR, 2022

2021

New Trends in Quantum Machine Learning.

Lorenzo Buffoni, Filippo Caruso

CoRR, 2021

On the training of sparse and dense deep neural networks: less parameters, same performance.

Lorenzo Chicchi, Lorenzo Giambagli, Lorenzo Buffoni, Timoteo Carletti, Marco Ciavarella, Duccio Fanelli

CoRR, 2021

Network-based link prediction of scientific concepts - a Science4Cast competition entry.

João P. Moutinho, Bruno C. Coutinho, Lorenzo Buffoni

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

A path towards quantum advantage in training deep generative models with quantum annealers.

Walter Winci, Lorenzo Buffoni, Hossein Sadeghi, Amir Khoshaman, Evgeny Andriyash, Mohammad H. Amin

Mach. Learn. Sci. Technol., 2020

Machine learning in spectral domain.

Lorenzo Giambagli, Lorenzo Buffoni, Timoteo Carletti, Walter Nocentini, Duccio Fanelli

CoRR, 2020

2019

A Path Towards Quantum Advantage in Training Deep Generative Models with Quantum Annealers.

Walter Vinci, Lorenzo Buffoni, Hossein Sadeghi, Amir Khoshaman, Evgeny Andriyash, Mohammad H. Amin

CoRR, 2019

PixelVAE++: Improved PixelVAE with Discrete Prior.

Hossein Sadeghi, Evgeny Andriyash, Walter Vinci, Lorenzo Buffoni, Mohammad H. Amin

CoRR, 2019