Sciweavers

21 search results - page 1 / 5
» Recursive Neural Networks and Graphs: Dealing with Cycles
Sort
View
WIRN
2005
Springer
13 years 9 months ago
Recursive Neural Networks and Graphs: Dealing with Cycles
Recursive neural networks are a powerful tool for processing structured data. According to the recursive learning paradigm, the input information consists of directed positional ac...
Monica Bianchini, Marco Gori, Lorenzo Sarti, Franc...
IJCNN
2006
IEEE
13 years 9 months ago
A Comparison between Recursive Neural Networks and Graph Neural Networks
— Recursive Neural Networks (RNNs) and Graph Neural Networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing fram...
Vincenzo Di Massa, Gabriele Monfardini, Lorenzo Sa...
ESANN
2004
13 years 5 months ago
Neural methods for non-standard data
Standard pattern recognition provides effective and noise-tolerant tools for machine learning tasks; however, most approaches only deal with real vectors of a finite and fixed dime...
Barbara Hammer, Brijnesh J. Jain
ICANN
2007
Springer
13 years 9 months ago
Recursive Principal Component Analysis of Graphs
Treatment of general structured information by neural networks is an emerging research topic. Here we show how representations for graphs preserving all the information can be devi...
Alessio Micheli, Alessandro Sperduti
ICPR
2006
IEEE
14 years 4 months ago
Object Localization Using Input/Output Recursive Neural Networks
Localizing objects in images is a difficult task and represents the first step to the solution of the object recognition problem. This paper presents a novel approach to the local...
Lorenzo Sarti, Marco Maggini, Monica Bianchini