320 citations · 740 across the 21 of their papers we have counts for
4 papers · 1 filter
Comparison between DeepESNs and gated RNNs on multivariate time-series prediction
Claudio Gallicchio, Alessio Micheli, Luca Pedrelli
We propose an experimental comparison between Deep Echo State Networks (DeepESNs) and gated Recurrent Neural Networks (RNNs) on multivariate time-series prediction tasks. In partic…
Tree Edit Distance Learning via Adaptive Symbol Embeddings
Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli +1
Metric learning has the aim to improve classification accuracy by learning a distance measure which brings data points from the same class closer together and pushes data points fr…
Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing
Davide Bacciu, Federico Errica, Alessio Micheli
We introduce the Contextual Graph Markov Model, an approach combining ideas from generative models and neural networks for the processing of graph data. It founds on a constructive…
Deep Echo State Networks for Diagnosis of Parkinson's Disease
Claudio Gallicchio, Alessio Micheli, Luca Pedrelli
In this paper, we introduce a novel approach for diagnosis of Parkinson's Disease (PD) based on deep Echo State Networks (ESNs). The identification of PD is performed by analyzing…