Stefano Melacci

research

∙ 09/13/2023

Collectionless Artificial Intelligence

By and large, the professional handling of huge data collections is rega...

0 Marco Gori, et al. ∙

research

∙ 06/05/2023

Continual Learning with Pretrained Backbones by Tuning in the Input Space

The intrinsic difficulty in adapting deep learning models to non-station...

0 Simone Marullo, et al. ∙

research

∙ 10/17/2022

PARTIME: Scalable and Parallel Processing Over Time with Deep Neural Networks

In this paper, we present PARTIME, a software library written in Python ...

16 Enrico Meloni, et al. ∙

research

∙ 09/19/2022

Concept Embedding Models

Deploying AI-powered systems requires trustworthy models supporting effe...

0 Mateo Espinosa Zarlenga, et al. ∙

research

∙ 08/08/2022

Learning to Identify Drilling Defects in Turbine Blades with Single Stage Detectors

Nondestructive testing (NDT) is widely applied to defect identification ...

0 Andrea Panizza, et al. ∙

research

∙ 06/30/2022

Deep Learning to See: Towards New Foundations of Computer Vision

The remarkable progress in computer vision over the last few years is, b...

0 Alessandro Betti, et al. ∙

research

∙ 04/26/2022

Stochastic Coherence Over Attention Trajectory For Continuous Learning In Video Streams

Devising intelligent agents able to live in an environment and learn by ...

2 Matteo Tiezzi, et al. ∙

research

∙ 12/18/2021

Being Friends Instead of Adversaries: Deep Networks Learn from Data Simplified by Other Networks

Amongst a variety of approaches aimed at making the learning procedure o...

5 Simone Marullo, et al. ∙

research

∙ 10/12/2021

Can machines learn to see without visual databases?

This paper sustains the position that the time has come for thinking of ...

0 Alessandro Betti, et al. ∙

research

∙ 09/17/2021

Messing Up 3D Virtual Environments: Transferable Adversarial 3D Objects

In the last few years, the scientific community showed a remarkable and ...

9 Enrico Meloni, et al. ∙

research

∙ 09/16/2021

Evaluating Continual Learning Algorithms by Generating 3D Virtual Environments

Continual learning refers to the ability of humans and animals to increm...

16 Enrico Meloni, et al. ∙

research

∙ 08/11/2021

Logic Explained Networks

The large and still increasing popularity of deep learning clashes with ...

12 Gabriele Ciravegna, et al. ∙

research

∙ 06/21/2021

Friendly Training: Neural Networks Can Adapt Data To Make Learning Easier

In the last decade, motivated by the success of Deep Learning, the scien...

16 Simone Marullo, et al. ∙

research

∙ 06/12/2021

Entropy-based Logic Explanations of Neural Networks

Explainable artificial intelligence has rapidly emerged since lawmakers ...

0 Pietro Barbiero, et al. ∙

research

∙ 02/08/2021

Generate and Revise: Reinforcement Learning in Neural Poetry

Writers, poets, singers usually do not create their compositions in just...

28 Andrea Zugarini, et al. ∙

research

∙ 09/15/2020

Gravitational Models Explain Shifts on Human Visual Attention

Visual attention refers to the human brain's ability to select relevant ...

0 Dario Zanca, et al. ∙

research

∙ 09/01/2020

Developing Constrained Neural Units Over Time

In this paper we present a foundational study on a constrained method th...

0 Alessandro Betti, et al. ∙

research

∙ 07/16/2020

SAILenv: Learning in Virtual Visual Environments Made Simple

Recently, researchers in Machine Learning algorithms, Computer Vision sc...

10 Enrico Meloni, et al. ∙

research

∙ 06/19/2020

Wave Propagation of Visual Stimuli in Focus of Attention

Fast reactions to changes in the surrounding visual environment require ...

0 Lapo Faggi, et al. ∙

research

∙ 06/16/2020

Focus of Attention Improves Information Transfer in Visual Features

Unsupervised learning from continuous visual streams is a challenging pr...

10 Matteo Tiezzi, et al. ∙

research

∙ 06/06/2020

Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers?

Adversarial attacks on machine learning-based classifiers, along with de...

16 Stefano Melacci, et al. ∙

research

∙ 05/05/2020

Deep Lagrangian Constraint-based Propagation in Graph Neural Networks

Several real-world applications are characterized by data that exhibit a...

12 Matteo Tiezzi, et al. ∙

research

∙ 02/18/2020

Local Propagation in Constraint-based Neural Network

In this paper we study a constraint-based representation of neural netwo...

8 Giuseppe Marra, et al. ∙

research

∙ 02/18/2020

A Lagrangian Approach to Information Propagation in Graph Neural Networks

In many real world applications, data are characterized by a complex str...

11 Matteo Tiezzi, et al. ∙

research

∙ 02/11/2020

Toward Improving the Evaluation of Visual Attention Models: a Crowdsourcing Approach

Human visual attention is a complex phenomenon. A computational modeling...

0 Dario Zanca, et al. ∙

research

∙ 11/13/2019

Asynchronous Distributed Learning from Constraints

In this paper, the extension of the framework of Learning from Constrain...

0 Francesco Farina, et al. ∙

research

∙ 09/24/2019

Jointly Learning to Detect Emotions and Predict Facebook Reactions

The growing ubiquity of Social Media data offers an attractive perspecti...

0 Lisa Graziani, et al. ∙

research

∙ 09/06/2019

Learning in Text Streams: Discovery and Disambiguation of Entity and Relation Instances

We consider a scenario where an artificial agent is reading a stream of ...

0 Marco Maggini, et al. ∙

research

∙ 09/01/2019

Learning Visual Features Under Motion Invariance

Humans are continuously exposed to a stream of visual data with a natura...

0 Alessandro Betti, et al. ∙

research

∙ 08/23/2019

Neural Poetry: Learning to Generate Poems using Syllables

Motivated by the recent progresses on machine learning-based models that...

0 Andrea Zugarini, et al. ∙

research

∙ 07/19/2019

An Unsupervised Character-Aware Neural Approach to Word and Context Representation Learning

In the last few years, neural networks have been intensively used to dev...

0 Giuseppe Marra, et al. ∙

research

∙ 10/17/2018

Coherence Constraints in Facial Expression Recognition

Recognizing facial expressions from static images or video sequences is ...

0 Lisa Graziani, et al. ∙

research

∙ 08/28/2018

Cognitive Action Laws: The Case of Visual Features

This paper proposes a theory for understanding perceptual learning proce...

14 Alessandro Betti, et al. ∙

research

∙ 07/14/2018

Motion Invariance in Visual Environments

The puzzle of computer vision might find new challenging solutions when ...

0 Alessandro Betti, et al. ∙

research

∙ 08/11/2014

Learning to see like children: proof of concept

In the last few years we have seen a growing interest in machine learnin...

0 Marco Gori, et al. ∙

research

∙ 09/29/2009

Laplacian Support Vector Machines Trained in the Primal

In the last few years, due to the growing ubiquity of unlabeled data, mu...

0 Stefano Melacci, et al. ∙

Stefano Melacci

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