Assessment of sequential Boltmann machines on a lexical processing task. - Alberto Testolin; Alessandro Sperduti; Ivilin Peev Stoianov; Marco Zorzi (ESANN, 2012)

A HMM-based pre-training approach for sequential data. - Luca Pasa; Alberto Testolin; Alessandro Sperduti (ESANN, 2014)

A machine learning approach to QoE-based video admission control and resource allocation in wireless systems. - Alberto Testolin; Marco Zanforlin; Michele De Filippo De Grazia; Daniele Munaretto; Andrea Zanella; Marco Zorzi; Michele Zorzi (Med-Hoc-Net, 2014)

Cognition-based networks: Applying cognitive science to multimedia wireless networking. - Leonardo Badia; Daniele Munaretto; Alberto Testolin; Andrea Zanella; Marco Zorzi; Michele Zorzi (WoWMoM, 2014)

Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence. - Michele Zorzi; Andrea Zanella; Alberto Testolin; Michele De Filippo De Grazia; Marco Zorzi (IEEE Access, 2015)

Neural Networks for Sequential Data: a Pre-training Approach based on Hidden Markov Models. - Luca Pasa; Alberto Testolin; Alessandro Sperduti (Neurocomputing, 2015)

COBANETS: A new paradigm for cognitive communications systems. - Michele Zorzi; Andrea Zanella; Alberto Testolin; Michele De Filippo De Grazia; Marco Zorzi (ICNC, 2016)

Learning Orthographic Structure With Sequential Generative Neural Networks. - Alberto Testolin; Ivilin Peev Stoianov; Alessandro Sperduti; Marco Zorzi (Cogn. Sci., 2016)

Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions. - Alberto Testolin; Marco Zorzi (Frontiers Comput. Neurosci., 2016)

Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning. - Zahra Sadeghi; Alberto Testolin (Cogn. Process., 2017)

The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding. - Alberto Testolin; Michele De Filippo De Grazia; Marco Zorzi (Frontiers Comput. Neurosci., 2017)

On the Relationship Between the Underwater Acoustic and Optical Channels. - Roee Diamant; Filippo Campagnaro; Michele De Filippo De Grazia; Paolo Casari; Alberto Testolin; Violeta Sanjuan Calzado; Michele Zorzi (IEEE Trans. Wirel. Commun., 2017)

Deep learning systems as complex networks. - Alberto Testolin; Michele Piccolini; Samir Suweis (CoRR, 2018)

QoE Multi-Stage Machine Learning for Dynamic Video Streaming. - Michele De Filippo De Grazia; Daniel Zucchetto; Alberto Testolin; Andrea Zanella; Marco Zorzi; Michele Zorzi (IEEE Trans. Cogn. Commun. Netw., 2018)

Underwater Acoustic Detection and Localization with a Convolutional Denoising Autoencoder. - Alberto Testolin; Roee Diamant (CAMSAP, 2019)

Enabling Simulation-Based Optimization through Machine Learning: A Case Study on Antenna Design. - Paolo Testolina; Mattia Lecci; Mattia Rebato; Alberto Testolin; Jonathan Gambini; Roberto Flamini; Christian Mazzucco; Michele Zorzi (GLOBECOM, 2019)

Numerosity Representation in InfoGAN: An Empirical Study. - Andrea Zanetti; Alberto Testolin; Marco Zorzi; Pawel Wawrzynski (IWANN (2), 2019)

Perception of visual numerosity in humans and machines. - Alberto Testolin; Serena Dolfi; Mathijs Rochus; Marco Zorzi (CoRR, 2019)

On the difficulty of learning and predicting the long-term dynamics of bouncing objects. - Alberto Cenzato; Alberto Testolin; Marco Zorzi (CoRR, 2019)

A Systematic Assessment of Feature Extraction Methods for Robust Prediction of Neuropsychological Scores from Functional Connectivity Data. - Federico Calesella; Alberto Testolin; Michele De Filippo De Grazia; Marco Zorzi (BI, 2020)

Distributed reinforcement learning for flexible UAV swarm control with transfer learning capabilities. - Federico Venturini; Federico Mason; Francesco Pase; Federico Chiariotti; Alberto Testolin; Andrea Zanella; Michele Zorzi (DroNet@MobiSys, 2020)

Long-Term Prediction of Physical Interactions: A Challenge for Deep Generative Models. - Alberto Cenzato; Alberto Testolin; Marco Zorzi (LOD (1), 2020)

Machine Learning-aided Design of Thinned Antenna Arrays for Optimized Network Level Performance. - Mattia Lecci; Paolo Testolina; Mattia Rebato; Alberto Testolin; Michele Zorzi (CoRR, 2020)

Emergence of Network Motifs in Deep Neural Networks. - Matteo Zambra; Amos Maritan; Alberto Testolin (Entropy, 2020)

Combining Denoising Autoencoders and Dynamic Programming for Acoustic Detection and Tracking of Underwater Moving Targets. - Alberto Testolin; Roee Diamant (Sensors, 2020)

Assessment of Machine Learning Pipelines for Prediction of Behavioral Deficits from Brain Disconnectomes. - Marco Zorzi; Michele De Filippo De Grazia; Elvio Blini; Alberto Testolin (BI, 2021)

A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients. - Federico Calesella; Alberto Testolin; Michele De Filippo De Grazia; Marco Zorzi (Brain Informatics, 2021)

Learning Numerosity Representations with Transformers: Number Generation Tasks and Out-of-Distribution Generalization. - Tommaso Boccato; Alberto Testolin; Marco Zorzi (Entropy, 2021)

Distributed Reinforcement Learning for Flexible and Efficient UAV Swarm Control. - Federico Venturini; Federico Mason; Francesco Pase; Federico Chiariotti; Alberto Testolin; Andrea Zanella; Michele Zorzi (IEEE Trans. Cogn. Commun. Netw., 2021)

Prediction of Neuropsychological Scores from Functional Connectivity Matrices Using Deep Autoencoders. - Delfina Irarte; Alberto Testolin; Michele De Filippo De Grazia; Marco Zorzi (BI, 2022)

Transformers discover an elementary calculation system exploiting local attention and grid-like problem representation. - Samuel Cognolato; Alberto Testolin (IJCNN, 2022)

Self-Communicating Deep Reinforcement Learning Agents Develop External Number Representations. - Silvester Sabathiel; Trygve Solstad; Alberto Testolin; Flavio Petruzzellis (NLDL, 2022)

A developmental approach for training deep belief networks. - Matteo Zambra; Alberto Testolin; Michele De Filippo De Grazia; Marco Zorzi (CoRR, 2022)

Detecting Submerged Objects Using Active Acoustics and Deep Neural Networks: A Test Case for Pelagic Fish. - Alberto Testolin; Dror Kipnis; Roee Diamant (IEEE Trans. Mob. Comput., 2022)

Learning Constraints From Human Stop-Feedback in Reinforcement Learning. - Silvia Poletti; Alberto Testolin; Sebastian Tschiatschek (AAMAS, 2023)

Investigating the Generative Dynamics of Energy-Based Neural Networks. - Lorenzo Tausani; Alberto Testolin; Marco Zorzi (BI, 2023)

A Hybrid System for Systematic Generalization in Simple Arithmetic Problems. - Flavio Petruzzellis; Alberto Testolin; Alessandro Sperduti (NeSy, 2023)

Learning to solve arithmetic problems with a virtual abacus. - Flavio Petruzzellis; Ling Xuan Chen; Alberto Testolin (NLDL, 2023)

AUV navigation using cues in the sand ripples. - Hadar Shalev; Liav Nagar; Avi Abu; Alberto Testolin; Roee Diamant (Auton. Robots, 2023)

Can neural networks do arithmetic? A survey on the elementary numerical skills of state-of-the-art deep learning models. - Alberto Testolin (CoRR, 2023)

A Developmental Approach for Training Deep Belief Networks. - Matteo Zambra; Alberto Testolin; Marco Zorzi (Cogn. Comput., 2023)

Automated detection of dolphin whistles with convolutional networks and transfer learning. - Burla Nur Korkmaz; Roee Diamant; Gil Danino; Alberto Testolin (Frontiers Artif. Intell., 2023)

FORTE: Few Samples for Recognizing Hand Gestures with a Smartphone-attached Radar. - Stefano Chioccarello; Arthur Sluÿters; Alberto Testolin; Jean Vanderdonckt; Sébastien Lambot (Proc. ACM Hum. Comput. Interact., 2023)

A Comparison of Recurrent and Convolutional Deep Learning Architectures for EEG Seizure Forecasting. - Sina Shafiezadeh; Marco Pozza; Alberto Testolin (BIOSTEC (1), 2024)

Benchmarking GPT-4 on Algorithmic Problems: A Systematic Evaluation of Prompting Strategies. - Flavio Petruzzellis; Alberto Testolin; Alessandro Sperduti (LREC/COLING, 2024)

A Neural Rewriting System to Solve Algorithmic Problems. - Flavio Petruzzellis; Alberto Testolin; Alessandro Sperduti (ECAI, 2024)

Relative Local Signal Strength: The Impact of Normalization on the Analysis of Neuroimaging Data with Deep Learning. - Giovanni Donghi; Luca Pasa; Alberto Testolin; Marco Zorzi; Alessandro Sperduti; Nicolò Navarin (ICANN (8), 2024)

Assessing the Emergent Symbolic Reasoning Abilities of Llama Large Language Models. - Flavio Petruzzellis; Alberto Testolin; Alessandro Sperduti (ICANN (5), 2024)

Exploiting Large Language Models to Train Automatic Detectors of Sensitive Data. - Simone De Renzis; Dennis Dosso; Alberto Testolin (IRCDL, 2024)

Investigation of a Neural Network for Dolphin Whistle Detection Through Heatmaps. - Jurica Jerinic; Alberto Testolin; Roee Diamant (WUWNet, 2024)

Large-scale Generative AI Models Lack Visual Number Sense. - Alberto Testolin; Kuinan Hou; Marco Zorzi (CoRR, 2024)

Estimating the distribution of numerosity and non-numerical visual magnitudes in natural scenes using computer vision. - Kuinan Hou; Marco Zorzi; Alberto Testolin (CoRR, 2024)

Calibrating Deep Learning Classifiers for Patient-Independent Electroencephalogram Seizure Forecasting. - Sina Shafiezadeh; Gian Marco Duma; Giovanni Mento; Alberto Danieli; Lisa Antoniazzi; Fiorella Del Popolo Cristaldi; Paolo Bonanni; Alberto Testolin (Sensors, 2024)

Artificial Intelligence Can Emulate Human Normative Judgments on Emotional Visual Scenes. - Zaira Romeo; Alberto Testolin (CoRR, 2025)

Learning neuro-symbolic convergent term rewriting systems. - Flavio Petruzzellis; Alberto Testolin; Alessandro Sperduti (CoRR, 2025)