Matching of time-varying labeled graphs. - Filippo Maria Bianchi; Lorenzo Livi; Antonello Rizzi (IJCNN, 2013)

Dissimilarity space embedding of labeled graphs by a clustering-based compression procedure. - Lorenzo Livi; Filippo Maria Bianchi; Antonello Rizzi; Alireza Sadeghian (IJCNN, 2013)

An interpretable graph-based image classifier. - Filippo Maria Bianchi; Simone Scardapane; Lorenzo Livi; Aurelio Uncini; Antonello Rizzi (IJCNN, 2014)

A Granular Computing approach to the design of optimized graph classification systems. - Filippo Maria Bianchi; Lorenzo Livi; Antonello Rizzi; Alireza Sadeghian (Soft Comput., 2014)

Short-Term Electric Load Forecasting Using Echo State Networks and PCA Decomposition. - Filippo Maria Bianchi; Enrico De Santis; Antonello Rizzi; Alireza Sadeghian (IEEE Access, 2015)

Position paper: a general framework for applying machine learning techniques in operating room. - Filippo Maria Bianchi; Enrico De Santis; Hedieh Montazeri; Parisa Naraei; Alireza Sadeghian (CoRR, 2015)

Prediction of telephone calls load using Echo State Network with exogenous variables. - Filippo Maria Bianchi; Simone Scardapane; Aurelio Uncini; Antonello Rizzi; Alireza Sadeghian (Neural Networks, 2015)

Granular Computing Techniques for Classification and Semantic Characterization of Structured Data. - Filippo Maria Bianchi; Simone Scardapane; Antonello Rizzi; Aurelio Uncini; Alireza Sadeghian (Cogn. Comput., 2016)

Multiplex visibility graphs to investigate recurrent neural networks dynamics. - Filippo Maria Bianchi; Lorenzo Livi; Cesare Alippi; Robert Jenssen (CoRR, 2016)

Identifying user habits through data mining on call data records. - Filippo Maria Bianchi; Antonello Rizzi; Alireza Sadeghian; Corrado Moiso (Eng. Appl. Artif. Intell., 2016)

Two density-based k-means initialization algorithms for non-metric data clustering. - Filippo Maria Bianchi; Lorenzo Livi; Antonello Rizzi (Pattern Anal. Appl., 2016)

Temporal overdrive recurrent neural network. - Filippo Maria Bianchi; Michael Kampffmeyer; Enrico Maiorino; Robert Jenssen (IJCNN, 2017)

Critical echo state network dynamics by means of Fisher information maximization. - Filippo Maria Bianchi; Lorenzo Livi; Robert Jenssen; Cesare Alippi (IJCNN, 2017)

Local short term electricity load forecasting: Automatic approaches. - The-Hien Dang-Ha; Filippo Maria Bianchi; Roland Olsson 001 (IJCNN, 2017)

Deep divergence-based clustering. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt-Børre Salberg; Robert Jenssen (MLSP, 2017)

The time series cluster kernel. - Karl Øyvind Mikalsen; Filippo Maria Bianchi; Cristina Soguero-Ruíz; Robert Jenssen (MLSP, 2017)

Deep Kernelized Autoencoders. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen; Lorenzo Livi (SCIA (1), 2017)

Spectral Clustering Using PCKID - A Probabilistic Cluster Kernel for Incomplete Data. - Sigurd Løkse; Filippo Maria Bianchi; Arnt-Børre Salberg; Robert Jenssen (SCIA (1), 2017)

A Clustering Approach to Heterogeneous Change Detection. - Luigi Tommaso Luppino; Stian Normann Anfinsen; Gabriele Moser; Robert Jenssen; Filippo Maria Bianchi; Sebastiano B. Serpico; Grégoire Mercier (SCIA (2), 2017)

Training Echo State Networks with Regularization Through Dimensionality Reduction. - Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen (Cogn. Comput., 2017)

Advances in Biologically Inspired Reservoir Computing. - Simone Scardapane; John B. Butcher; Filippo Maria Bianchi; Zeeshan Khawar Malik (Cogn. Comput., 2017)

An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting. - Filippo Maria Bianchi; Enrico Maiorino; Michael C. Kampffmeyer; Antonello Rizzi; Robert Jenssen (CoRR, 2017)

Bidirectional deep echo state networks. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (CoRR, 2017)

A novel algorithm for online inexact string matching and its FPGA implementation. - Alessandro Cinti; Filippo Maria Bianchi; Antonello Rizzi (CoRR, 2017)

Data-driven detrending of nonstationary fractal time series with echo state networks. - Enrico Maiorino; Filippo Maria Bianchi; Lorenzo Livi; Antonello Rizzi; Alireza Sadeghian (Inf. Sci., 2017)

An agent-based algorithm exploiting multiple local dissimilarities for clusters mining and knowledge discovery. - Filippo Maria Bianchi; Enrico Maiorino; Lorenzo Livi; Antonello Rizzi; Alireza Sadeghian (Soft Comput., 2017)

Recurrent Neural Networks for Short-Term Load Forecasting - An Overview and Comparative Analysis - Filippo Maria Bianchi; Enrico Maiorino; Michael C. Kampffmeyer; Antonello Rizzi; Robert Jenssen (Springer, 2017)

Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. - Andreas Storvik Strauman; Filippo Maria Bianchi; Karl Øyvind Mikalsen; Michael Kampffmeyer; Cristina Soguero-Ruíz; Robert Jenssen (BHI, 2018)

On the Interpretation and Characterization of Echo State Networks Dynamics: A Complex Systems Perspective. - Filippo Maria Bianchi; Lorenzo Livi; Cesare Alippi (Advances in Data Analysis with Computational Intelligence Methods, 2018)

Learning compressed representations of blood samples time series with missing data. - Filippo Maria Bianchi; Karl Øyvind Mikalsen; Robert Jenssen (ESANN, 2018)

Bidirectional deep-readout echo state networks. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (ESANN, 2018)

Time Series Kernel Similarities for Predicting Paroxysmal Atrial Fibrillation from ECGs. - Filippo Maria Bianchi; Lorenzo Livi; Alberto Ferrante; Jelena Milosevic; Miroslaw Malek (IJCNN, 2018)

Remote Sensing Image Regression for Heterogeneous Change Detection. - Luigi Tommaso Luppino; Filippo Maria Bianchi; Gabriele Moser; Stian Normann Anfinsen (MLSP, 2018)

The deep kernelized autoencoder. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen; Lorenzo Livi (Appl. Soft Comput., 2018)

An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; Filippo Maria Bianchi; Arthur Revhaug; Robert Jenssen (CoRR, 2018)

Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders. - Filippo Maria Bianchi; Lorenzo Livi; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen (CoRR, 2018)

Time series cluster kernel for learning similarities between multivariate time series with missing data. - Karl Øyvind Mikalsen; Filippo Maria Bianchi; Cristina Soguero-Ruíz; Robert Jenssen (Pattern Recognit., 2018)

Investigating Echo-State Networks Dynamics by Means of Recurrence Analysis. - Filippo Maria Bianchi; Lorenzo Livi; Cesare Alippi (IEEE Trans. Neural Networks Learn. Syst., 2018)

Determination of the Edge of Criticality in Echo State Networks Through Fisher Information Maximization. - Lorenzo Livi; Filippo Maria Bianchi; Cesare Alippi (IEEE Trans. Neural Networks Learn. Syst., 2018)

Mincut pooling in Graph Neural Networks. - Filippo Maria Bianchi; Daniele Grattarola; Cesare Alippi (CoRR, 2019)

Deep divergence-based approach to clustering. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt-Børre Salberg; Robert Jenssen (Neural Networks, 2019)

Learning representations of multivariate time series with missing data. - Filippo Maria Bianchi; Lorenzo Livi; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen (Pattern Recognit., 2019)

Noisy multi-label semi-supervised dimensionality reduction. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; Filippo Maria Bianchi; Robert Jenssen (Pattern Recognit., 2019)

Unsupervised Image Regression for Heterogeneous Change Detection. - Luigi Tommaso Luppino; Filippo Maria Bianchi; Gabriele Moser; Stian Normann Anfinsen (IEEE Trans. Geosci. Remote. Sens., 2019)

Pyramidal Graph Echo State Networks. - Filippo Maria Bianchi; Claudio Gallicchio; Alessio Micheli (ESANN, 2020)

Spectral Clustering with Graph Neural Networks for Graph Pooling. - Filippo Maria Bianchi; Daniele Grattarola; Cesare Alippi (ICML, 2020)

Non-iterative Learning Approaches and Their Applications. - Filippo Maria Bianchi; Ponnuthurai Nagaratnam Suganthan (Cogn. Comput., 2020)

A Novel Algorithm for Online Inexact String Matching and its FPGA Implementation. - Alessandro Cinti; Filippo Maria Bianchi; Alessio Martino; Antonello Rizzi (Cogn. Comput., 2020)

Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning. - Filippo Maria Bianchi; Martine Mostervik Espeseth; Njål Borch (Remote. Sens., 2020)

Deep learning for graphs. - Davide Bacciu; Filippo Maria Bianchi; Benjamin Paassen; Cesare Alippi (ESANN, 2021)

Towards Applicability: A Comparative Study on Non-Intrusive Load Monitoring Algorithms. - Huamin Ren; Filippo Maria Bianchi; Jingyue Li; Rasmus L. Olsen; Robert Jenssen; Stian Normann Anfinsen (ICCE, 2021)

Detecting the Linear and Non-linear Causal Links for Disturbances in the Power Grid. - Odin Foldvik Eikeland; Filippo Maria Bianchi; Inga Setså Holmstrand; Sigurd Bakkejord; Matteo Chiesa (INTAP, 2021)

Detecting and Interpreting Faults in Vulnerable Power Grids With Machine Learning. - Odin Foldvik Eikeland; Inga Setså Holmstrand; Sigurd Bakkejord; Matteo Chiesa; Filippo Maria Bianchi (IEEE Access, 2021)

Power Flow Balancing with Decentralized Graph Neural Networks. - Jonas Berg Hansen; Stian Normann Anfinsen; Filippo Maria Bianchi (CoRR, 2021)

Time series cluster kernels to exploit informative missingness and incomplete label information. - Karl Øyvind Mikalsen; Cristina Soguero-Ruíz; Filippo Maria Bianchi; Arthur Revhaug; Robert Jenssen (Pattern Recognit., 2021)

Snow Avalanche Segmentation in SAR Images With Fully Convolutional Neural Networks. - Filippo Maria Bianchi; Jakob Grahn; Markus Eckerstorfer; Eirik Malnes; Hannah Vickers (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (IEEE Trans. Neural Networks Learn. Syst., 2021)

Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case. - Odin Foldvik Eikeland; Finn Dag Hovem; Tom Eirik Olsen; Matteo Chiesa; Filippo Maria Bianchi (CoRR, 2022)

Clustering with Total Variation Graph Neural Networks. - Jonas Berg Hansen; Filippo Maria Bianchi (CoRR, 2022)

Pyramidal Reservoir Graph Neural Network. - Filippo Maria Bianchi; Claudio Gallicchio; Alessio Micheli (Neurocomputing, 2022)

Graph Neural Networks With Convolutional ARMA Filters. - Filippo Maria Bianchi; Daniele Grattarola; Lorenzo Livi; Cesare Alippi (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Recognition of Polar Lows in Sentinel-1 SAR Images With Deep Learning. - Jakob Grahn; Filippo Maria Bianchi (IEEE Trans. Geosci. Remote. Sens., 2022)

Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection. - Luigi Tommaso Luppino; Michael Kampffmeyer; Filippo Maria Bianchi; Gabriele Moser; Sebastiano Bruno Serpico; Robert Jenssen; Stian Normann Anfinsen (IEEE Trans. Geosci. Remote. Sens., 2022)

Hierarchical Representation Learning in Graph Neural Networks With Node Decimation Pooling. - Filippo Maria Bianchi; Daniele Grattarola; Lorenzo Livi; Cesare Alippi (IEEE Trans. Neural Networks Learn. Syst., 2022)

Scalable Spatiotemporal Graph Neural Networks. - Andrea Cini; Ivan Marisca; Filippo Maria Bianchi; Cesare Alippi (AAAI, 2023)

Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability. - Indro Spinelli; Michele Guerra; Filippo Maria Bianchi; Simone Scardapane (ESANN, 2023)

Total Variation Graph Neural Networks. - Jonas Berg Hansen; Filippo Maria Bianchi (ICML, 2023)

The expressive power of pooling in Graph Neural Networks. - Filippo Maria Bianchi; Veronica Lachi (NeurIPS, 2023)

Simplifying Clustering with Graph Neural Networks. - Filippo Maria Bianchi (NLDL, 2023)

Explainability in subgraphs-enhanced Graph Neural Networks. - Michele Guerra; Indro Spinelli; Simone Scardapane; Filippo Maria Bianchi (NLDL, 2023)

Probabilistic Load Forecasting With Reservoir Computing. - Michele Guerra; Simone Scardapane; Filippo Maria Bianchi (IEEE Access, 2023)

Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling. - Ivan Marisca; Cesare Alippi; Filippo Maria Bianchi (ICML, 2024)

Interpreting Temporal Graph Neural Networks with Koopman Theory. - Michele Guerra; Simone Scardapane; Filippo Maria Bianchi (CoRR, 2024)

Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images. - Luigi Tommaso Luppino; Mads A. Hansen; Michael Kampffmeyer; Filippo Maria Bianchi; Gabriele Moser; Robert Jenssen; Stian Normann Anfinsen (IEEE Trans. Neural Networks Learn. Syst., 2024)

Understanding Pooling in Graph Neural Networks. - Daniele Grattarola; Daniele Zambon; Filippo Maria Bianchi; Cesare Alippi (IEEE Trans. Neural Networks Learn. Syst., 2024)

Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting. - Vilde Jensen; Filippo Maria Bianchi; Stian Normann Anfinsen (IEEE Trans. Neural Networks Learn. Syst., 2024)

MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks. - Carlo Abate; Filippo Maria Bianchi (ICLR, 2025)

On Time Series Clustering with Graph Neural Networks. - Jonas Berg Hansen; Andrea Cini; Filippo Maria Bianchi (Trans. Mach. Learn. Res., 2025)

BN-Pool: a Bayesian Nonparametric Approach to Graph Pooling. - Daniele Castellana; Filippo Maria Bianchi (CoRR, 2025)

Relational Conformal Prediction for Correlated Time Series. - Andrea Cini; Alexander Jenkins; Danilo P. Mandic; Cesare Alippi; Filippo Maria Bianchi (CoRR, 2025)

Monitoring snow avalanches from SAR data with deep learning. - Filippo Maria Bianchi; Jakob Grahn (CoRR, 2025)