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09/13/2023
Collectionless Artificial Intelligence
By and large, the professional handling of huge data collections is rega...
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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...
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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 ...
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08/08/2022
Learning to Identify Drilling Defects in Turbine Blades with Single Stage Detectors
Nondestructive testing (NDT) is widely applied to defect identification ...
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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...
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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...
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10/15/2021
Knowledge-driven Active Learning
In the last few years, Deep Learning models have become increasingly pop...
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10/13/2021
Logic Constraints to Feature Importances
In recent years, Artificial Intelligence (AI) algorithms have been prove...
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10/13/2021
Clustering-Based Interpretation of Deep ReLU Network
Amongst others, the adoption of Rectified Linear Units (ReLUs) is regard...
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10/12/2021
Can machines learn to see without visual databases?
This paper sustains the position that the time has come for thinking of ...
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09/21/2021
Graph Neural Networks for Graph Drawing
Graph Drawing techniques have been developed in the last few years with ...
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09/17/2021
Messing Up 3D Virtual Environments: Transferable Adversarial 3D Objects
In the last few years, the scientific community showed a remarkable and ...
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08/11/2021
Logic Explained Networks
The large and still increasing popularity of deep learning clashes with ...
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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...
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06/12/2021
Entropy-based Logic Explanations of Neural Networks
Explainable artificial intelligence has rapidly emerged since lawmakers ...
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10/28/2020
An Optimal Control Approach to Learning in SIDARTHE Epidemic model
The COVID-19 outbreak has stimulated the interest in the proposal of nov...
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09/15/2020
Gravitational Models Explain Shifts on Human Visual Attention
Visual attention refers to the human brain's ability to select relevant ...
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09/01/2020
Developing Constrained Neural Units Over Time
In this paper we present a foundational study on a constrained method th...
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08/14/2020
An Overview on the Web of Clinical Data
In the last few years there has been an impressive growth of connections...
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07/16/2020
SAILenv: Learning in Virtual Visual Environments Made Simple
Recently, researchers in Machine Learning algorithms, Computer Vision sc...
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06/19/2020
Wave Propagation of Visual Stimuli in Focus of Attention
Fast reactions to changes in the surrounding visual environment require ...
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06/16/2020
Focus of Attention Improves Information Transfer in Visual Features
Unsupervised learning from continuous visual streams is a challenging pr...
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06/06/2020
Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers?
Adversarial attacks on machine learning-based classifiers, along with de...
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02/29/2020
Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective
Neural-symbolic computing has now become the subject of interest of both...
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02/18/2020
Local Propagation in Constraint-based Neural Network
In this paper we study a constraint-based representation of neural netwo...
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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...
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02/11/2020
Toward Improving the Evaluation of Visual Attention Models: a Crowdsourcing Approach
Human visual attention is a complex phenomenon. A computational modeling...
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02/06/2020
Relational Neural Machines
Deep learning has been shown to achieve impressive results in several ta...
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12/10/2019
Backprop Diffusion is Biologically Plausible
The Backpropagation algorithm relies on the abstraction of using a neura...
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11/21/2019
Discrete and Continuous Deep Residual Learning Over Graphs
In this paper we propose the use of continuous residual modules for grap...
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09/24/2019
Jointly Learning to Detect Emotions and Predict Facebook Reactions
The growing ubiquity of Social Media data offers an attractive perspecti...
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09/01/2019
Learning Visual Features Under Motion Invariance
Humans are continuously exposed to a stream of visual data with a natura...
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07/26/2019
Learning and T-Norms Theory
Deep learning has been shown to achieve impressive results in several do...
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07/18/2019
On the relation between Loss Functions and T-Norms
Deep learning has been shown to achieve impressive results in several do...
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07/14/2019
On the Role of Time in Learning
By and large the process of learning concepts that are embedded in time ...
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07/11/2019
Spatiotemporal Local Propagation
This paper proposes an in-depth re-thinking of neural computation that p...
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07/04/2019
Least Action Principles and Well-Posed Learning Problems
Machine Learning algorithms are typically regarded as appropriate optimi...
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05/15/2019
Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning
Current advances in Artificial Intelligence and machine learning in gene...
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03/18/2019
LYRICS: a General Interface Layer to Integrate AI and Deep Learning
In spite of the amazing results obtained by deep learning in many applic...
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01/23/2019
Typed Graph Networks
Recently, the deep learning community has given growing attention to neu...
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01/14/2019
Integrating Learning and Reasoning with Deep Logic Models
Deep learning is very effective at jointly learning feature representati...
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10/17/2018
Coherence Constraints in Facial Expression Recognition
Recognizing facial expressions from static images or video sequences is ...
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09/18/2018
On a Convex Logic Fragment for Learning and Reasoning
In this paper we introduce the convex fragment of Łukasiewicz Logic and ...
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08/28/2018
Cognitive Action Laws: The Case of Visual Features
This paper proposes a theory for understanding perceptual learning proce...
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08/21/2018
Backpropagation and Biological Plausibility
By and large, Backpropagation (BP) is regarded as one of the most import...
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07/17/2018
Learning Neuron Non-Linearities with Kernel-Based Deep Neural Networks
The effectiveness of deep neural architectures has been widely supported...
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07/16/2018
Constraint-Based Visual Generation
In the last few years the systematic adoption of deep learning to visual...
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07/14/2018
Motion Invariance in Visual Environments
The puzzle of computer vision might find new challenging solutions when ...
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07/14/2018
Generalization in quasi-periodic environments
By and large the behavior of stochastic gradient is regarded as a challe...
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07/11/2018
