M. Guerra, S. Scardapane, F. M. Bianchi, "Probabilistic load forecasting with Reservoir Computing", IEEE Access, 2023. [Link][Preprint][Code]

K. Ingebrigtsen, F. M. Bianchi, S. Bakkejord, I. S. Holmstrand, M. Chiesa, "Identifying Conditions Leading to Power Quality Events in Arctic Norway: Feature Selection",  Applied Energy, Elsevier, 2023. [Link]

O. F. Eikeland, C. C. Kelsall, K. Buznitsky, S. Verma, F. M. Bianchi, M. Chiesa, A. Henry, "Power Availability of PV plus Thermal Batteries in real-world electric power grids", Applied Energy, Elsevier, 2023. [Link][Preprint]

V. Jensen, F. M. Bianchi, S. N. Anfinsen, "Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting", Transactions on Neural Networks and Learning Systems, IEEE, 2022. [Link][Preprint][Code]

I. Martinsen, A. Harbitz, F. M. Bianchi, "Age prediction by deep learning applied to Greenland halibut (Reinhardtius hippoglossoides) otolith images", PLOS One, 2022. [Link][Code]

J. Grahn and F. M. Bianchi, "Recognition of polar lows in Sentinel-1 SAR images with deep learning", Transactions on Geoscience and Remote Sensing, IEEE, 2022. [Link][Preprint][Code][Dataset]

J. Berg Hansen, S. N. Anfinsen, F. M. Bianchi, "Power Flow Balancing with Decentralized Graph Neural Networks", Transactions on Power Systems, IEEE, 2022. [Link][Preprint][Code]

D. Grattarola, D. Zambon, F. M. Bianchi, C. Alippi, "Understanding Pooling in Graph Neural Networks", Transactions on Neural Networks and Learning Systems, IEEE, 2022. [Link][Preprint][Code]

O. F. Eikeland, F. D. Hovem, T. E. Olsen, M. Chiesa, F. M. Bianchi, "Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case", Energy Conversion and Management: X, Elsevier, 2022. [Link][Preprint]

L. T. Luppino, M. A. Hansen, M. Kampffmeyer, F. M. Bianchi, G. Moser, R. Jenssen, S. N. Anfinsen, "Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images", Transactions on Neural Networks and Learning Systems, IEEE, 2022. [Link][Preprint]

O. F. Eikeland, F. M. Bianchi, I. S. Holmstrand, S. Bakkejord, S. Santos, M. Chiesa, "Uncovering contributing factors to interruptions in the power grid: An Arctic case", Energies, MDPI, 2021. [Link][Preprint]

O. F. Eikeland, I. S. Holmstrand, S. Bakkejord, M. Chiesa, F. M. Bianchi, "Detecting and interpreting faults in vulnerable power grids with machine learning", IEEE Access, 2021. [Link][Preprint][Code]

F. M. Bianchi, D. Grattarola, L. Livi, C. Alippi, "Graph Neural Networks with Convolutional ARMA Filters", Transactions on Pattern Analysis and Machine Intelligence, IEEE, 2021. [Link][Preprint][Code]

F. M. Bianchi, C. Gallicchio, A. Micheli, "Pyramidal Reservoir Graph Neural Network", Neurocomputing, Elsevier, 2021. [Link][Preprint][Code][Dataset]

M. Rypdal, K. Rypdal, O. Løvsletten, S. H. Sørbye, E. Ytterstad, F. M. Bianchi, "Estimation of excess mortality and years of life lost to COVID-19 in Norway and Sweden between March and November 2020", International Journal of Environmental Research and Public Health, MDPI, 2021. [Link]

K. Ø. Mikalsen, C. Soguero-Ruiz, F. M. Bianchi, A. Revhaug, R. Jenssen, "Time series cluster kernels to exploit informative missingness and incomplete label information", Pattern Recognition, Elsevier,  2021. [Link][Preprint]

L. T. Luppino, M. Kampffmeyer, F. M. Bianchi, G. Moser, S. B. Serpico, R. Jenssen, S. N. Anfinsen, "Deep Image Translation with an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection",  Transactions on Geoscience and Remote Sensing, IEEE, 2021. [Link][Preprint]

O. F. Eikeland, F. M. Bianchi, H. Apostoleris, M. Hansen, Y. Chiou, M. Chiesa, "Predicting Energy Demand in Semi-Remote Arctic Locations", Energies, MDPI, 2021. [Link]

F. M. Bianchi, D. Grattarola, L. Livi, C. Alippi, "Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling",  Transactions on Neural Networks and Learning Systems, IEEE, 2020. [Link][Preprint][Code]

K. Rypdal, F. M. Bianchi, M. Rypdal, "Intervention fatigue is the primary cause of strong secondary waves in the COVID-19 pandemic", International Journal of Environmental Research and Public Health, MDPI, 2020. [Link][Preprint]

F. M. Bianchi, J. Grahn, M. Eckerstorfer, E. Malnes, H. Vickers, "Snow avalanche segmentation in SAR images with Fully Convolutional Neural Networks", Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2020. [Link][Preprint]

F. M. Bianchi, M. M. Espeseth, N. Borch, "Large-scale detection and categorization of oil spills from SAR images with deep learning ", Remote Sensing, MDPI, 2020. [Link][Preprint]

F. M. Bianchi, S. Scardapane, S. Løkse, R. Jenssen, "Reservoir computing approaches for representation and classification of multivariate time series", Transactions on Neural Networks and Learning Systems, IEEE, 2020. [Link][Preprint][Code]

L. T. Luppino, F. M. Bianchi, G. Moser, S. N. Anfinsen, "Unsupervised Image Regression for Heterogeneous Change Detection", Transactions on Geoscience and Remote Sensing, IEEE, 2019. [Link][Preprint]

F. M. Bianchi, L. Livi, K. Ø. Mikalsen, M. Kampffmeyer, R. Jenssen, "Learning representations for multivariate time series with missing data", Pattern Recognition, Elsevier, 2019. [Link][Preprint][Code]

A. Cinti, F. M. Bianchi, A. Martino, A. Rizzi, "A novel algorithm for online inexact string matching and its FPGA implementation", Cognitive Computation, Springer, 2019. [Link][Preprint][Code]

R. Kube, F. M. Bianchi, D. Brunner, B. LaBombard, "Outlier classification using Autoencoders: application for fluctuation driven flows in fusion plasmas", Review of Scientific Instruments, AIP, 2019. [Link][Preprint]

K. Ø Mikalsen, C. Soguero-Ruiz, F. M. Bianchi, R. Jenssen "Noisy multi-label semi-supervised dimensionality reduction", Pattern Recognition, Elsevier, 2019. [Link][Preprint]

M. Kampffmeyer, S. Løkse, F. M. Bianchi, L. Livi, R. Jenssen "Deep Divergence-Based Approach to Clustering ", Neural Networks, Elsevier, 2019. [Link][Preprint]

M. Kampffmeyer, S. Løkse, F. M. Bianchi, R. Jenssen, L. Livi, "The Deep Kernelized Autoencoder", Applied Soft Computing, Elsevier, 2018. [Link][Preprint]

K. Ø. Mikalsen, F. M. Bianchi, C. Soguero-Ruiz, R. Jenssen, "Time Series Cluster Kernel for Learning Similarities between Multivariate Time Series with Missing Data". Pattern Recognition, Elsevier, 2017. [Link][Preprint][Code]

F. M. Bianchi, L. Livi, C. Alippi, R. Jenssen, "Multiplex visibility graphs to investigate recurrent neural networks dynamics". Scientific Reports, Nature, 2017. [Link]

L. Livi, F. M. Bianchi, C. Alippi, "Determination of the edge of criticality in echo state networks through Fisher information maximization". Transactions on Neural Networks and Learning Systems, IEEE, 2018. [Link][Preprint]

S. Løkse, F. M. Bianchi, R. Jenssen, "Training Echo State Networks with Regularization through Dimensionality Reduction". SI: Advances in Biologically Inspired Reservoir Computing, Cognitive Computation, Springer, 2017. [Link][Preprint][Code]

E. Maiorino, F. M. Bianchi, L. Livi, A. Rizzi, A. Sadeghian, "Data-driven detrending of nonstationary fractal time series with echo state networks". Information Sciences, Elsevier, 2017. [Link][Preprint][Code]

F. M. Bianchi, A. Rizzi, A. Sadeghian, C. Moiso, "Identifying user habits through data mining on call data records". Engineering Applications of Artificial Intelligence, Elsevier, 2016. [Link][Preprint][Code]

F. M. Bianchi, L. Livi, C. Alippi, "Investigating echo state networks dynamics by means of recurrence analysis". Transactions on Neural Networks and Learning Systems, IEEE, 2018. [Link][Preprint][Code]

F. M. Bianchi, S. Scardapane, A. Uncini, A. Rizzi, A. Sadeghian, "Prediction of telephone calls load using Echo State Network with exogenous variables", Neural Networks, Elsevier, 2015. [Link][Preprint]

F. M. Bianchi, S. Scardapane, A. Rizzi, A. Uncini, A. Sadeghian, "Granular Computing Techniques for Classification and Semantic Characterization of Structured Data". Cognitive Computation, Springer, 2015. [Link][Preprint]

F. M. Bianchi, E. De Santis, A. Rizzi, A. Sadeghian, "Short-Term Electric Load Forecasting Using Echo State Networks and PCA Decomposition", IEEE Access, IEEE, 2015. [Link]

F. M. Bianchi, E. Maiorino, L. Livi, A. Rizzi, A. Sadeghian, "An Agent-Based Algorithm exploiting Multiple Local Dissimilarities for Clusters Mining and Knowledge Discovery", Soft Computing, Springer, 2015. [Link][Preprint][Code]

F. M. Bianchi, L. Livi, A. Rizzi, "Two density-based k-means initialization algorithms for non-metric data clustering", Pattern Analysis and Applications, Springer, 2014. [Link][Preprint]

F. M.  Bianchi, L. Livi, A. Rizzi, A. Sadeghian, "A Granular Computing approach to the design of optimized graph classification systems", Soft Computing, Springer, 2013. [Link][Preprint][Code]

I. Marisca, C. Alippi, F. M. Bianchi, "Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling", International Conference on Machine Learning (ICML), 2024. [Preprint]

F. M. Bianchi, V. Lachi, "The expressive power of pooling in Graph Neural Networks", Advances in Neural Information Processing Systems (NeurIPS), 2023. [Preprint][Code][Poster]

J. Berg Hansen, F. M. Bianchi, "Total Variation Graph Neural Networks", International Conference on Machine Learning (ICML), 2023. [Link][Preprint][Code][Poster]

A. Cini, I. Marisca, F. M. Bianchi, C. Alippi, "Scalable Spatiotemporal Graph Neural Networks", AAAI Conference on Artificial Intelligence, 2023. [Link][Preprint][Code][Poster]

I. Spinelli, M. Guerra, F. M. Bianchi, S. Scardapane, "Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability", European Symposium on Artificial Neural Networks (ESANN), 2023. [Preprint]

M. Guerra, I. Spinelli, S. Scardapane, F. M. Bianchi, "Explainability in subgraphs-enhanced Graph Neural Networks", Northern Lights Deep Learning Conference (NLDL), 2023. [Link][Preprint][Code]

F. M. Bianchi, "Simplifying Clustering with Graph Neural Networks", Northern Lights Deep Learning Conference (NLDL), 2023. [Link][Preprint][Code][Poster]

D. Bacciu, F. M. Bianchi, B. Paassen, C. Alippi, "Deep learning for graphs", European Symposium on Artificial Neural Networks (ESANN), 2021. [Link]

A. G. Imenes, N. S. Noori, O. A. N. Uthaug, R. Kröni, F. M. Bianchi, N, Belbachir, "A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites",  IEEE 48th Photovoltaic Specialists Conference, 2021. [Link]

O. F. Eikeland, F. M. Bianchi, I. S. Holmstrand, S. Bakkejord, M. Chiesa, "Detecting the linear and non-linear causal links for disturbances in the power grid",  International Conference on Intelligent Technologies and Applications (INTAP), 2021. [Link]

H. Ren, F. M. Bianchi, J. Li, R. L. Olsen, R. Jenssen, S. N. Anfinsen, "Towards Applicability: A Comparative Study on Non-Intrusive Load Monitoring Algorithms", IEEE International Conference on Consumer Electronics, 2021. [Link]

F. M. Bianchi, D. Grattarola, C. Alippi, "Spectral Clustering with Graph Neural Networks for Graph Pooling ", International Conference on Machine Learning (ICML), 2020. [Link][Preprint][Code][Presentation]

N. S. Noori, F. M. Bianchi, T. I. Waag, "Condition Monitoring System for Internal Blowout Prevention (IBOP) in Top Drive Assembly System using Discrete Event Systems and Deep Learning Approaches", PHM Society European Conference, 2020. [Link]

F. M. Bianchi, C. Gallicchio, A. Micheli, "Pyramidal Graph Echo State Networks", European Symposium on Artificial Neural Networks (ESANN), 2020. [Link][Code]

C. Choi, F. M. Bianchi, M. Kampffmeyer, R. Jenssen, "Short-Term Load Forecasting with Dilated Recurrent Attention Networks in Presence of Missing Data", Northern Lights Deep Learning Conference (NLDL), 2020. [Link][Preprint]

L. T. Luppino, F. M. Bianchi, G. Moser, S. N. Anfinsen, "Remote sensing image regression for heterogeneous change detection", IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2018. [Link][Preprint][Poster]

F. M. Bianchi, L. Livi, A. Ferrante, J. Milosevic, M. Malek, "Time series kernel similarities for predicting Paroxysmal Atrial Fibrillation from ECGs", IEEE World Congress on Computational Intelligence (WCCI), 2018. [Link][Preprint][Presentation]

P. E. Kummervold, E. Malnes, M. Eckerstorfer, I. M. Arntzen, F. M. Bianchi, "Avalanche detection in Sentinel-1 radar images using Convolutional Neural Networks", International Snow Science Workshop (ISSW), 2018. [Link]

F. M. Bianchi, S. Scardapane, S. Løkse, R. Jenssen, "Bidirectional Deep-readout Echo State Networks", European Symposium on Artificial Neural Networks (ESANN), 2018. [Link][Preprint][Code][Presentation]

F. M. Bianchi, K. Ø. Mikalsen, R. Jenssen, "Learning compressed representations of blood samples time series with missing data", European Symposium on Artificial Neural Networks (ESANN), 2018. [Link][Preprint][Code][Presentation]

A. S. Strauman, F. M. Bianchi, K. Ø. Mikalsen, M. Kampffmeyer, C. Soguero-Ruiz, R. Jenssen, "Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks", Biomedical and Health Informatics (BHI), 2017. [Link][Preprint][Poster]

M. Kampffmeyer, S. Løkse, F. M. Bianchi, L. Livi, A. Salberg, R. Jenssen "Deep Divergence-Based Clustering". IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2017. [Link][Preprint][Presentation]

K. Ø. Mikalsen, F. M. Bianchi, C. Soguero-Ruiz, R. Jenssen, "The Time Series Cluster Kernel". IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2017. [Link][Presentation][Code]

D.H. The-Hien, F. M. Bianchi, R. Olsson, "Local Short Term Electricity Load Forecasting: Automatic Approaches". International Joint Conference on Neural Networks (IJCNN), 2017. [Link][Preprint][Presentation]

S. Løkse, F. M. Bianchi, A.B. Salberg, R. Jenssen, "Spectral Clustering using PCKID - A Probabilistic Cluster Kernel for Incomplete Data". Image Analysis: 20th Scandinavian Conference (SCIA), Scandinavian Conference on Image Analysis, 2017.  [Link][Preprint][Presentation]

L. T. Luppino, S. N. Anfinsen, G. Moser, R. Jenssen, F. M. Bianchi, S. Serpico, G. Mercier, "A clustering approach to heterogeneous change detection". Image Analysis: 20th Scandinavian Conference, Scandinavian Conference on Image Analysis (SCIA), 2017. [Link][Preprint][Poster]

M. Kampffmeyer, S. Løkse, F. M. Bianchi, R. Jenssen and L. Livi, "Deep Kernelized Autoencoders". Image Analysis: 20th Scandinavian Conference, Scandinavian Conference on Image Analysis (SCIA), 2017. [Link][Preprint][Presentation]

F. M. Bianchi, M. Kampffmeyer, E. Maiorino, R. Jenssen, "Temporal Overdrive Recurrent Neural Network". International Joint Conference on Neural Networks (IJCNN), 2017. [Link][Preprint][Presentation]

F. M. Bianchi, L. Livi, R. Jenssen, C. Alippi, "Critical echo state network dynamics by means of Fisher information maximization". International Joint Conference on Neural Networks (IJCNN), 2017. [Link][Preprint][Poster]

K. Ø. Mikalsen, F. M. Bianchi, C. Soguero-Ruiz, S. O. Skrøvseth, R. O. Lindsetmo, A. Revhaug, R. Jenssen, "Learning similarities between irregularly sampled short multivariate time series from EHRs". International Conference on Pattern Recognition, 2016. [Link]

F. M. Bianchi, S. Scardapane, L. Livi, A. Uncini, A. Rizzi, "An interpretable graph-based image classifier", IEEE World Congress on Computational Intelligence (WCCI), 2014. [Link][Preprint]

F. M. Bianchi, L. Livi, A. Rizzi, "Matching of time-varying labeled graphs", International Joint Conference on Neural Networks (IJCNN), 2013. [Link][Preprint]

L. Livi, F. M. Bianchi, A. Rizzi, A. Sadeghian, "Dissimilarity space embedding of labeled graphs by a clustering-based compression procedure", International Joint Conference on Neural Networks (IJCNN), 2013. [Link][Preprint]

F. M. Bianchi, E. Maiorino, M. Kampffmeyer, A. Rizzi, R. Jenssen, "Recurrent Neural Networks for Short-Term Load Forecasting: An Overview and Comparative Analysis", Briefs in Computer Sciences, Springer, 2017. [Link][Preprint]

F. M. Bianchi, L. Livi, C. Alippi, "On the interpretation and characterization of echo state networks dynamics: A complex systems perspective". Advances in Data Analysis with Computational Intelligence Methods, Springer, 2018. [Link][Preprint]

F. M. Bianchi, P. N. Suganthan, "Non-iterative Learning Approaches and Their Applications ", Cognitive Computation, Springer, 2020. [Link]

S. Scardapane, J. B Butcher, F. M. Bianchi, Z. K Malik, "Advances in Biologically Inspired Reservoir Computing", Cognitive Computation, Springer, 2017. [Link]

P. Sharma and F. M. Bianchi, "Proceedings of 20th Scandinavian Conference on Image Analysis, SCIA 2017", Tromsø, Norway, June 12–14, 2017, Part I & II. [Link1][Link2]

K. Ø. Mikalsen, C. Soguero-Ruiz, F. M. Bianchi, Arthur Revhaug and Robert Jenssen, "An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples", 2018. [Preprint]

F. M. Bianchi, E. De Santis, H. Montazeri, P. Naraei, and A. Sadeghian, "Position paper: a general framework for applying machine learning techniques in operating room", 2015. [Preprint]