Michele Mancusi

According to our database, Michele Mancusi authored at least 16 papers between 2021 and 2026.

Collaborative distances:

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

2026

PHALAR: Phasors for Learned Musical Audio Representations.

Davide Marincione, Michele Mancusi, Giorgio Strano, Luca Cerovaz, Donato Crisostomi, Roberto Ribuoli, Emanuele Rodolà

CoRR, May, 2026

EuleroDec: A Complex-Valued RVQ-VAE for Efficient and Robust Audio Coding.

Luca Cerovaz, Michele Mancusi, Emanuele Rodolà

CoRR, January, 2026

SteerMusic: Enhanced Musical Consistency for Zero-shot Text-Guided and Personalized Music Editing.

Xinlei Niu, Kin Wai Cheuk, Jing Zhang, Naoki Murata, Chieh-Hsin Lai, Michele Mancusi, Woosung Choi, Giorgio Fabbro, Wei-Hsiang Liao, Charles Patrick Martin, Yuki Mitsufuji

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

STAGE: Stemmed Accompaniment Generation through Prefix-Based Conditioning.

Giorgio Strano, Chiara Ballanti, Donato Crisostomi, Michele Mancusi, Luca Cosmo, Emanuele Rodolà

Proceedings of the 26th International Society for Music Information Retrieval Conference, 2025

ITO-Master: Inference-Time Optimization for Audio Effects Modeling of Music Mastering Processors.

Junghyun Koo, Marco A. Martínez Ramírez, Wei-Hsiang Liao, Giorgio Fabbro, Michele Mancusi, Yuki Mitsufuji

Proceedings of the 26th International Society for Music Information Retrieval Conference, 2025

Latent Diffusion Bridges for Unsupervised Musical Audio Timbre Transfer.

Michele Mancusi, Yurii Halychanskyi, Kin Wai Cheuk, Eloi Moliner, Chieh-Hsin Lai, Stefan Uhlich, Junghyun Koo, Marco A. Martínez Ramírez, Wei-Hsiang Liao, Giorgio Fabbro, Yuki Mitsufuji

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

High-Resolution Speech Restoration with Latent Diffusion Model.

Tushar Dhyani, Florian Lux, Michele Mancusi, Giorgio Fabbro, Fritz Hohl, Ngoc Thang Vu

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

COCOLA: Coherence-Oriented Contrastive Learning of Musical Audio Representations.

Ruben Ciranni, Giorgio Mariani, Michele Mancusi, Emilian Postolache, Giorgio Fabbro, Emanuele Rodolà, Luca Cosmo

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024

Latent Diffusion Bridges for Unsupervised Musical Audio Timbre Transfer.

Michele Mancusi, Yurii Halychanskyi, Kin Wai Cheuk, Chieh-Hsin Lai, Stefan Uhlich, Junghyun Koo, Marco A. Martínez Ramírez, Wei-Hsiang Liao, Giorgio Fabbro, Yuki Mitsufuji

CoRR, 2024

COCOLA: Coherence-Oriented Contrastive Learning of Musical Audio Representations.

Ruben Ciranni, Emilian Postolache, Giorgio Mariani, Michele Mancusi, Luca Cosmo, Emanuele Rodolà

CoRR, 2024

Multi-Source Diffusion Models for Simultaneous Music Generation and Separation.

Giorgio Mariani, Irene Tallini, Emilian Postolache, Michele Mancusi, Luca Cosmo, Emanuele Rodolà

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Exploiting Music Source Separation For Singing Voice Detection.

Francesco Bonzi, Michele Mancusi, Simone Del Deo, Pierfrancesco Melucci, Maria Stella Tavella, Loreto Parisi, Emanuele Rodolà

Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Accelerating Transformer Inference for Translation via Parallel Decoding.

Andrea Santilli, Silvio Severino, Emilian Postolache, Valentino Maiorca, Michele Mancusi, Riccardo Marin, Emanuele Rodolà

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Latent Autoregressive Source Separation.

Emilian Postolache, Giorgio Mariani, Michele Mancusi, Andrea Santilli, Luca Cosmo, Emanuele Rodolà

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Fish sounds: towards the evaluation of marine acoustic biodiversity through data-driven audio source separation.

Michele Mancusi, Nicola Zonca, Emanuele Rodolà, Silvia Zuffi

CoRR, 2022

2021

Unsupervised Source Separation via Bayesian Inference in the Latent Domain.

Michele Mancusi, Emilian Postolache, Marco Fumero, Andrea Santilli, Luca Cosmo, Emanuele Rodolà

CoRR, 2021