Publications

• E. Grassucci, J. Choi, J. Park, R. F. Gramaccioni, G. Cicchetti, D. Comminiello, Rethinking Multi-User Semantic Communications with Deep Generative Models, under review in Journal on Selected Areas on Communications. [Preprint]

• G. Cicchetti, E. Grassucci, J. Park, S. Barbarossa, D. Comminiello, Language-Oriented Semantic Latent Representation for Image Transmission, under review. [Preprint]

• E. Grassucci, J. Park, S. Barbarossa, S.-L. Kim, J. Choi, D. Comminiello, Generative AI Meets Semantic Communication: Evolution and Revolution of Communication Tasks, under review. [Preprint]

• E. Grassucci, S. Barbarossa, D. Comminiello, Generative Semantic Communication: Diffusion Models Beyond Bit Recovery, under review. [Preprint][GitHub]

• E. Lopez, E. Grassucci, M. Valleriani, D. Comminiello, Hypercomplex Neural Architectures for Multi-View Breast Cancer Classification, April 2022. Submitted to IEEE Trans. on Pattern Analysis and Machine Intelligence. [Preprint][GitHub] 

• L. Sigillo, E. Grassucci, A. Uncini, D. Comminiello,Generalizing Medical Image Representations via Quaternion Wavelet Networks, Oct 2023, under review. [Preprint]

• D. Comminiello, E. Grassucci, D. P. Mandic, A. Uncini, Demystifying the Hypercomplex: Inductive Biases in Hypercomplex Deep Learning, March. 2023. IEEE Signal Processing Magazine. [Preprint]

• E. Lopez, F. Betello, F. Carmignani, E. Grassucci, D. Comminiello, Attention-map augmentation for hypercomplex breast cancer classification, May 2024, Pattern Recognition Letters. [Paper]

• E. Grassucci, L. Sigillo, A. Uncini, and D. Comminiello, GROUSE: A Task and Model Agnostic Wavelet-Driven Framework for Medical Imaging, Oct. 2023, IEEE Signal Processing Letters. [IEEEXplore]

• S. Barbarossa, D. Comminiello, E. Grassucci, F. Pezone, S. Sardellitti, P. Di Lorenzo, Semantic communications Based on Adaptive Generative Models and Information Bottleneck, IEEE Communications Magazine, vol. 61, n. 11, pp. 36-41, Nov 2023. [Paper]

• L. Parisi, S. Mulargia, F. Comunello, V. Bernardini, A. Bussoletti, C. R. Nisi, L. Russo, I. Campagna, B. Lanfranchi, I. Croci, E. Grassucci, F. Gesualdo, The vaccine conversation on TikTok in Italy: beyond classic vaccine stances, BC Public Health, April 2022.

• E. Grassucci, G. Mancini, C. Brignone, A. Uncini, and D. Comminiello, Dual Quaternion Ambisonics Array for Six-Degree-of-Freedom Acoustic Representation, Pattern Recognition Letters, 166, February 2023, pp.24-30. [Preprint][GitHub]

• E. Grassucci, A. Zhang, and D. Comminiello, PHNNs: Lightweight neural networks via parameterized hypercomplex convolutions, IEEE Trans. on Neural Netw. and Learning Systems (TNNLS), December 2022. [Paper] [Preprint] [GitHub]

• C. Brignone, G. Mancini, E. Grassucci, A. Uncini, D. Comminiello, Efficient sound event localization and detection in the quaternion domain,  IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 69, no. 5, pp. 2453-2457, May 2022. [Paper][Slides]

Awarded as Best Track Manuscript by the IEEE Circuits and Systems Society at IEEE ISCAS 2022!

• E. Grassucci, D. Comminiello, and A.Uncini, An Information-Theoretic Perspective on Proper Quaternion Variational Autoencoders, Entropy 23, no. 7: 856, July 2021. [Paper] [GitHub]

• E. Grassucci, E. Cicero and D. Comminiello, Quaternion Generative Adversarial Networks, in Generative Adversarial Learning:  Architectures and Applications, R. Razavi-Far, A. Ruiz-Garcia, V. Palade, and J. Schmidhuber, Springer International Publishing, pp. 57–86, January 2022. [Paper] [Preprint] [GitHub]

• E. Grassucci, S. Scardapane, D. Comminiello, and A. Uncini, Flexible Generative Adversarial Networks with Non-Parametric Activation Functions, in Progress in Artificial Intelligence and Neural Systems, (Anna Esposito, Marcos Faundez-Zanuy, Francesco Carlo Morabito, Eros Pasero, Eds.), vol. 184 of Smart Innovation, Systems and Technologies, Springer, 2021.

• E. Lopez, E. Grassucci, D. Comminiello, Towards Explaining Hypercomplex Neural Networks, IEEE WCCI 2024.

• J. Choi, J. Park, E. Grassucci, D. Comminiello, Semantic Communication Challenges: Understanding Dos and Avoiding Don’ts, IEEE VTC Spring 2024. [Preprint]

• E. Grassucci, C. Marinoni, A. Rodriguez, D. Comminiello, Diffusion models for audio semantic communication, IEEE ICASSP 2024. [Preprint][Paper on IEEEXplore][Project page][GitHub]

• E. Grassucci, Y. Mitsufuji, P. Zhang, D. Comminiello, Enhancing Semantic Communication with Deep Generative Models: An Overview, IEEE ICASSP 2024. [Preprint][Paper on IEEEXplore]

• M. Mancanelli, E. Grassucci, A. Uncini, and D. Comminiello, PHYDI: Initializing Parameterized Hypercomplex Neural Networks as Identity Functions, IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2023), Sept. 2023. [Preprint]

Honorable Top 5% Mention!

• L. Sigillo, A. Marzilli, D. Moretti, E. Grassucci, C. Greco, and D. Comminiello, Sailing the SeaFormer: A Transformer-Based Model for Vessel Route Forecasting, IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2023), Sept. 2023.

• G. Vieira, M. E. Valle, E. Grassucci, and D. Comminiello, Dual Quaternion Rotational and Translational Equivariance in 3D Rigid Motion Modelling, IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2023), Sept. 2023. [Preprint]

Honorable Top 10% Mention!

• E. Lopez, E. Chiarantano, E. Grassucci, and D. Comminiello, Hypercomplex Multimodal Emotion Recognition from EEG and Peripheral Physiological Signals, IEEE ICASSP, June 2023.

• L. Sigillo, E. Grassucci, and D. Comminiello, StawGAN: Structural-Aware Generative Adversarial Networks for Infrared Image Translation, IEEE Int. Symposium on Circuits and Systems. (ISCAS), Monterey, CA, USA, May 2023.

• E. Grassucci, L. Sigillo, A. Uncini, and D. Comminiello, Hypercomplex Image-to-Image Translation, IEEE Int. Joint Conf. on Neural Netw. (IJCNN), July 2022. [Preprint][GitHub]

• E. Grassucci, D. Comminiello, and A. Uncini, A Quaternion-valued Variational Autoencoder, IEEE ICASSP, June 2021, pp. 3310-3314. [Paper] [Preprint] [GitHub][Slides]