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[HTML][HTML] Synergies between machine learning and reasoning-An introduction by the Kay R. Amel group
This paper proposes a tentative and original survey of meeting points between Knowledge
Representation and Reasoning (KRR) and Machine Learning (ML), two areas which have …
Representation and Reasoning (KRR) and Machine Learning (ML), two areas which have …
Semantic loss: A new neuro-symbolic approach for context-aware human activity recognition
Deep Learning models are a standard solution for sensor-based Human Activity
Recognition (HAR), but their deployment is often limited by labeled data scarcity and …
Recognition (HAR), but their deployment is often limited by labeled data scarcity and …
Neuro-symbolic learning: Principles and applications in ophthalmology
M Hassan, H Guan, A Melliou, Y Wang, Q Sun… - ar** neuro-symbolic AI models
G Gronchi, A Perini - Frontiers in Cognition, 2024 - frontiersin.org
In recent years, subsymbolic-based artificial intelligence has developed significantly, both
from a theoretical and an applied perspective. OpenAI's Chat Generative Pre-trained …
from a theoretical and an applied perspective. OpenAI's Chat Generative Pre-trained …
[PDF][PDF] Neurosymbolic system profiling: A template-based approach.
Two antagonistic categories can be identified within Artificial Intelligence models: symbolic
and subsymbolic. Neurosymbolic artificial intelligence is the term used to describe a set of …
and subsymbolic. Neurosymbolic artificial intelligence is the term used to describe a set of …
[PDF][PDF] Artificial intelligence and robotics as the driving power of modern society
In synergy with other technologies, the AI significantly accelerates the scientific and
technological development of human society. New possibilities of the application of …
technological development of human society. New possibilities of the application of …
Umjetna inteligencija i robotika kao pokretačka snaga modernog društva
Sažetak U sinergiji s drugim tehnologijama AI značajno ubrzava znanstveni i tehnološki
razvoj ljudskog društva. Neprestano se otvaraju nove mogućnosti primjene tehnoloških …
razvoj ljudskog društva. Neprestano se otvaraju nove mogućnosti primjene tehnoloških …
Deep deductive reasoning is a hard deep learning problem
Abstract Deep Deductive Reasoning refers to the training and then executing of deep
learning systems to perform deductive reasoning in the sense of formal, mathematical logic …
learning systems to perform deductive reasoning in the sense of formal, mathematical logic …
[HTML][HTML] Reconfiguration of Hybrid Systems
K Balzereit - 2023 - publica.fraunhofer.de
Hybrid systems are characterized by a combination of discrete and continuous behavior.
Such hybrid systems are becoming more and more widespread, while constantly develo** …
Such hybrid systems are becoming more and more widespread, while constantly develo** …