Filippo Maria Bianchi

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 102

Top Venues

CoRR

IEEE Trans. Neural Networks Learn. Syst.

IJCNN

ESANN

Publications

Luigi Tommaso Luppino, Mads A. Hansen, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Robert Jenssen, Stian Normann Anfinsen
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images. IEEE Trans. Neural Networks Learn. Syst. 35 (1) (2024)
Vilde Jensen, Filippo Maria Bianchi, Stian Normann Anfinsen
Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting. IEEE Trans. Neural Networks Learn. Syst. 35 (7) (2024)
Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling. CoRR (2024)
Daniele Grattarola, Daniele Zambon, Filippo Maria Bianchi, Cesare Alippi
Understanding Pooling in Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35 (2) (2024)
Jonas Berg Hansen, Filippo Maria Bianchi
Total Variation Graph Neural Networks. ICML (2023)
Indro Spinelli, Michele Guerra, Filippo Maria Bianchi, Simone Scardapane
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability. ESANN (2023)
Filippo Maria Bianchi, Veronica Lachi
The expressive power of pooling in Graph Neural Networks. NeurIPS (2023)
Michele Guerra, Indro Spinelli, Simone Scardapane, Filippo Maria Bianchi
Explainability in subgraphs-enhanced Graph Neural Networks. NLDL (2023)
Michele Guerra, Simone Scardapane, Filippo Maria Bianchi
Probabilistic Load Forecasting With Reservoir Computing. IEEE Access 11 (2023)
Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi
Scalable Spatiotemporal Graph Neural Networks. AAAI (2023)
Filippo Maria Bianchi, Veronica Lachi
The expressive power of pooling in Graph Neural Networks. CoRR (2023)
Michele Guerra, Simone Scardapane, Filippo Maria Bianchi
Probabilistic load forecasting with Reservoir Computing. CoRR (2023)
Indro Spinelli, Michele Guerra, Filippo Maria Bianchi, Simone Scardapane
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability. CoRR (2023)
Filippo Maria Bianchi
Simplifying Clustering with Graph Neural Networks. NLDL (2023)
Vilde Jensen, Filippo Maria Bianchi, Stian Normann Anfinsen
Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting. CoRR (2022)
Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi
Scalable Spatiotemporal Graph Neural Networks. CoRR (2022)
Odin Foldvik Eikeland, Finn Dag Hovem, Tom Eirik Olsen, Matteo Chiesa, Filippo Maria Bianchi
Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case. CoRR (2022)
Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Sebastiano Bruno Serpico, Robert Jenssen, Stian Normann Anfinsen
Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi
Graph Neural Networks With Convolutional ARMA Filters. IEEE Trans. Pattern Anal. Mach. Intell. 44 (7) (2022)
Filippo Maria Bianchi, Claudio Gallicchio, Alessio Micheli
Pyramidal Reservoir Graph Neural Network. Neurocomputing 470 (2022)
Michele Guerra, Indro Spinelli, Simone Scardapane, Filippo Maria Bianchi
Explainability in subgraphs-enhanced Graph Neural Networks. CoRR (2022)
Jakob Grahn, Filippo Maria Bianchi
Recognition of polar lows in Sentinel-1 SAR images with deep learning. CoRR (2022)
Jakob Grahn, Filippo Maria Bianchi
Recognition of Polar Lows in Sentinel-1 SAR Images With Deep Learning. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Filippo Maria Bianchi
Simplifying Clustering with Graph Neural Networks. CoRR (2022)
Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi
Hierarchical Representation Learning in Graph Neural Networks With Node Decimation Pooling. IEEE Trans. Neural Networks Learn. Syst. 33 (5) (2022)
Jonas Berg Hansen, Filippo Maria Bianchi
Clustering with Total Variation Graph Neural Networks. CoRR (2022)
Filippo Maria Bianchi, Claudio Gallicchio, Alessio Micheli
Pyramidal Reservoir Graph Neural Network. CoRR (2021)
Odin Foldvik Eikeland, Inga Setså Holmstrand, Sigurd Bakkejord, Matteo Chiesa, Filippo Maria Bianchi
Detecting and Interpreting Faults in Vulnerable Power Grids With Machine Learning. IEEE Access 9 (2021)
Huamin Ren, Filippo Maria Bianchi, Jingyue Li, Rasmus L. Olsen, Robert Jenssen, Stian Normann Anfinsen
Towards Applicability: A Comparative Study on Non-Intrusive Load Monitoring Algorithms. ICCE (2021)
Daniele Grattarola, Daniele Zambon, Filippo Maria Bianchi, Cesare Alippi
Understanding Pooling in Graph Neural Networks. CoRR (2021)
Odin Foldvik Eikeland, Filippo Maria Bianchi, Inga Setså Holmstrand, Sigurd Bakkejord, Matteo Chiesa
Detecting the Linear and Non-linear Causal Links for Disturbances in the Power Grid. INTAP (2021)
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen
Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series. IEEE Trans. Neural Networks Learn. Syst. 32 (5) (2021)
Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen
Time series cluster kernels to exploit informative missingness and incomplete label information. Pattern Recognit. 115 (2021)
Filippo Maria Bianchi, Jakob Grahn, Markus Eckerstorfer, Eirik Malnes, Hannah Vickers
Snow Avalanche Segmentation in SAR Images With Fully Convolutional Neural Networks. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14 (2021)
Odin Foldvik Eikeland, Inga Setså Holmstrand, Sigurd Bakkejord, Matteo Chiesa, Filippo Maria Bianchi
Detecting and interpreting faults in vulnerable power grids with machine learning. CoRR (2021)
Jonas Berg Hansen, Stian Normann Anfinsen, Filippo Maria Bianchi
Power Flow Balancing with Decentralized Graph Neural Networks. CoRR (2021)
Davide Bacciu, Filippo Maria Bianchi, Benjamin Paassen, Cesare Alippi
Deep learning for graphs. ESANN (2021)
Filippo Maria Bianchi, Martine Mostervik Espeseth, Njål Borch
Large-scale detection and categorization of oil spills from SAR images with deep learning. CoRR (2020)
Filippo Maria Bianchi, Claudio Gallicchio, Alessio Micheli
Pyramidal Graph Echo State Networks. ESANN (2020)
Luigi Tommaso Luppino, Mads A. Hansen, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Robert Jenssen, Stian Normann Anfinsen
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images. CoRR (2020)
Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi
Spectral Clustering with Graph Neural Networks for Graph Pooling. ICML (2020)
Filippo Maria Bianchi, Martine Mostervik Espeseth, Njål Borch
Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning. Remote. Sens. 12 (14) (2020)
Filippo Maria Bianchi, Ponnuthurai Nagaratnam Suganthan
Non-iterative Learning Approaches and Their Applications. Cogn. Comput. 12 (2) (2020)
Alessandro Cinti, Filippo Maria Bianchi, Alessio Martino, Antonello Rizzi
A Novel Algorithm for Online Inexact String Matching and its FPGA Implementation. Cogn. Comput. 12 (2) (2020)
Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Sebastiano Bruno Serpico, Robert Jenssen, Stian Normann Anfinsen
Deep Image Translation with an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection. CoRR (2020)
Filippo Maria Bianchi, Lorenzo Livi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen
Learning representations of multivariate time series with missing data. Pattern Recognit. 96 (2019)
Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi
Graph Neural Networks with convolutional ARMA filters. CoRR (2019)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen
Deep Divergence-Based Approach to Clustering. CoRR (2019)
Filippo Maria Bianchi, Jakob Grahn, Markus Eckerstorfer, Eirik Malnes, Hannah Vickers
Snow avalanche segmentation in SAR images with Fully Convolutional Neural Networks. CoRR (2019)
Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Robert Jenssen
Noisy multi-label semi-supervised dimensionality reduction. Pattern Recognit. 90 (2019)
Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi
Mincut pooling in Graph Neural Networks. CoRR (2019)
Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen
Time series cluster kernels to exploit informative missingness and incomplete label information. CoRR (2019)
Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling. CoRR (2019)
Luigi Tommaso Luppino, Filippo Maria Bianchi, Gabriele Moser, Stian Normann Anfinsen
Unsupervised Image Regression for Heterogeneous Change Detection. IEEE Trans. Geosci. Remote. Sens. 57 (12) (2019)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen
Deep divergence-based approach to clustering. Neural Networks 113 (2019)
Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Robert Jenssen
Noisy multi-label semi-supervised dimensionality reduction. CoRR (2019)
Luigi Tommaso Luppino, Filippo Maria Bianchi, Gabriele Moser, Stian Normann Anfinsen
Unsupervised Image Regression for Heterogeneous Change Detection. CoRR (2019)
Filippo Maria Bianchi, Lorenzo Livi, Cesare Alippi
On the Interpretation and Characterization of Echo State Networks Dynamics: A Complex Systems Perspective. Advances in Data Analysis with Computational Intelligence Methods (2018)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi
The deep kernelized autoencoder. Appl. Soft Comput. 71 (2018)
Filippo Maria Bianchi, Lorenzo Livi, Alberto Ferrante, Jelena Milosevic, Miroslaw Malek
Time series kernel similarities for predicting Paroxysmal Atrial Fibrillation from ECGs. CoRR (2018)
Luigi Tommaso Luppino, Filippo Maria Bianchi, Gabriele Moser, Stian Normann Anfinsen
Remote sensing image regression for heterogeneous change detection. CoRR (2018)
Filippo Maria Bianchi, Lorenzo Livi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen
Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders. CoRR (2018)
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen
Reservoir computing approaches for representation and classification of multivariate time series. CoRR (2018)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi
The Deep Kernelized Autoencoder. CoRR (2018)
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen
Bidirectional deep-readout echo state networks. ESANN (2018)
Karl Øyvind Mikalsen, Cristina Soguero-Ruíz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen
An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples. CoRR (2018)
Filippo Maria Bianchi, Lorenzo Livi, Cesare Alippi
Investigating Echo-State Networks Dynamics by Means of Recurrence Analysis. IEEE Trans. Neural Networks Learn. Syst. 29 (2) (2018)
Filippo Maria Bianchi, Karl Øyvind Mikalsen, Robert Jenssen
Learning compressed representations of blood samples time series with missing data. ESANN (2018)
Karl Øyvind Mikalsen, Filippo Maria Bianchi, Cristina Soguero-Ruíz, Robert Jenssen
Time series cluster kernel for learning similarities between multivariate time series with missing data. Pattern Recognit. 76 (2018)
Filippo Maria Bianchi, Lorenzo Livi, Alberto Ferrante, Jelena Milosevic, Miroslaw Malek
Time Series Kernel Similarities for Predicting Paroxysmal Atrial Fibrillation from ECGs. IJCNN (2018)
Lorenzo Livi, Filippo Maria Bianchi, Cesare Alippi
Determination of the Edge of Criticality in Echo State Networks Through Fisher Information Maximization. IEEE Trans. Neural Networks Learn. Syst. 29 (3) (2018)
Luigi Tommaso Luppino, Filippo Maria Bianchi, Gabriele Moser, Stian Normann Anfinsen
Remote Sensing Image Regression for Heterogeneous Change Detection. MLSP (2018)
Andreas Storvik Strauman, Filippo Maria Bianchi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Cristina Soguero-Ruíz, Robert Jenssen
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. BHI (2018)
Filippo Maria Bianchi, Michael Kampffmeyer, Enrico Maiorino, Robert Jenssen
Temporal overdrive recurrent neural network. IJCNN (2017)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi
Deep Kernelized Autoencoders. CoRR (2017)
Luigi Tommaso Luppino, Stian Normann Anfinsen, Gabriele Moser, Robert Jenssen, Filippo Maria Bianchi, Sebastiano B. Serpico, Grégoire Mercier
A clustering approach to heterogeneous change detection. CoRR (2017)
Filippo Maria Bianchi, Enrico Maiorino, Lorenzo Livi, Antonello Rizzi, Alireza Sadeghian
An agent-based algorithm exploiting multiple local dissimilarities for clusters mining and knowledge discovery. Soft Comput. 21 (5) (2017)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi
Deep Kernelized Autoencoders. SCIA (1) (2017)
Andreas Storvik Strauman, Filippo Maria Bianchi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Cristina Soguero-Ruíz, Robert Jenssen
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. CoRR (2017)
Luigi Tommaso Luppino, Stian Normann Anfinsen, Gabriele Moser, Robert Jenssen, Filippo Maria Bianchi, Sebastiano B. Serpico, Grégoire Mercier
A Clustering Approach to Heterogeneous Change Detection. SCIA (2) (2017)
Filippo Maria Bianchi, Lorenzo Livi, Robert Jenssen, Cesare Alippi
Critical echo state network dynamics by means of Fisher information maximization. IJCNN (2017)
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen
Bidirectional deep echo state networks. CoRR (2017)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen
Deep divergence-based clustering. MLSP (2017)
Alessandro Cinti, Filippo Maria Bianchi, Antonello Rizzi
A novel algorithm for online inexact string matching and its FPGA implementation. CoRR (2017)
The-Hien Dang-Ha, Filippo Maria Bianchi, Roland Olsson
Local short term electricity load forecasting: Automatic approaches. IJCNN (2017)
Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen
Training Echo State Networks with Regularization Through Dimensionality Reduction. Cogn. Comput. 9 (3) (2017)
Enrico Maiorino, Filippo Maria Bianchi, Lorenzo Livi, Antonello Rizzi, Alireza Sadeghian
Data-driven detrending of nonstationary fractal time series with echo state networks. Inf. Sci. (2017)
Filippo Maria Bianchi, Enrico Maiorino, Michael C. Kampffmeyer, Antonello Rizzi, Robert Jenssen
An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting. CoRR (2017)
Sigurd Løkse, Filippo Maria Bianchi, Arnt-Børre Salberg, Robert Jenssen
Spectral Clustering Using PCKID - A Probabilistic Cluster Kernel for Incomplete Data. SCIA (1) (2017)
Filippo Maria Bianchi, Karl Øyvind Mikalsen, Robert Jenssen
Learning compressed representations of blood samples time series with missing data. CoRR (2017)
Filippo Maria Bianchi, Antonello Rizzi, Alireza Sadeghian, Corrado Moiso
Identifying user habits through data mining on call data records. CoRR (2017)
Karl Øyvind Mikalsen, Filippo Maria Bianchi, Cristina Soguero-Ruíz, Robert Jenssen
Time Series Cluster Kernel for Learning Similarities between Multivariate Time Series with Missing Data. CoRR (2017)
Filippo Maria Bianchi, Michael Kampffmeyer, Enrico Maiorino, Robert Jenssen
Temporal Overdrive Recurrent Neural Network. CoRR (2017)
Karl Øyvind Mikalsen, Filippo Maria Bianchi, Cristina Soguero-Ruíz, Robert Jenssen
The time series cluster kernel. MLSP (2017)
Simone Scardapane, John B. Butcher, Filippo Maria Bianchi, Zeeshan Khawar Malik
Advances in Biologically Inspired Reservoir Computing. Cogn. Comput. 9 (3) (2017)
Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen
Training Echo State Networks with Regularization through Dimensionality Reduction. CoRR (2016)
Filippo Maria Bianchi, Lorenzo Livi, Antonello Rizzi
Two density-based k-means initialization algorithms for non-metric data clustering. Pattern Anal. Appl. 19 (3) (2016)
Lorenzo Livi, Filippo Maria Bianchi, Cesare Alippi
Determination of the edge of criticality in echo state networks through Fisher information maximization. CoRR (2016)
Filippo Maria Bianchi, Simone Scardapane, Antonello Rizzi, Aurelio Uncini, Alireza Sadeghian
Granular Computing Techniques for Classification and Semantic Characterization of Structured Data. Cogn. Comput. 8 (3) (2016)
Filippo Maria Bianchi, Lorenzo Livi, Cesare Alippi
Investigating echo state networks dynamics by means of recurrence analysis. CoRR (2016)

Filippo Maria Bianchi.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Filippo Maria Bianchi