
From Statistical Relational to Neural Symbolic Artificial Intelligence: a Survey
Neuralsymbolic and statistical relational artificial intelligence both ...
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DeepStochLog: Neural Stochastic Logic Programming
Recent advances in neural symbolic learning, such as DeepProbLog, extend...
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Learning Representations for SubSymbolic Reasoning
Neurosymbolic methods integrate neural architectures, knowledge represe...
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Online Learning of NonMarkovian Reward Models
There are situations in which an agent should receive rewards only after...
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Deep Lagrangian Constraintbased Propagation in Graph Neural Networks
Several realworld applications are characterized by data that exhibit a...
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From Statistical Relational to NeuroSymbolic Artificial Intelligence
Neurosymbolic and statistical relational artificial intelligence both i...
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Local Propagation in Constraintbased Neural Network
In this paper we study a constraintbased representation of neural netwo...
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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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Relational Neural Machines
Deep learning has been shown to achieve impressive results in several ta...
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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 ...
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Learning and TNorms Theory
Deep learning has been shown to achieve impressive results in several do...
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An Unsupervised CharacterAware Neural Approach to Word and Context Representation Learning
In the last few years, neural networks have been intensively used to dev...
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On the relation between Loss Functions and TNorms
Deep learning has been shown to achieve impressive results in several do...
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Neural Markov Logic Networks
We introduce Neural Markov Logic Networks (NMLNs), a statistical relatio...
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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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Integrating Learning and Reasoning with Deep Logic Models
Deep learning is very effective at jointly learning feature representati...
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Backpropagation and Biological Plausibility
By and large, Backpropagation (BP) is regarded as one of the most import...
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Learning Neuron NonLinearities with KernelBased Deep Neural Networks
The effectiveness of deep neural architectures has been widely supported...
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ConstraintBased Visual Generation
In the last few years the systematic adoption of deep learning to visual...
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Giuseppe Marra
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