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  3. Filippo Maria Bianchi
Bilde av Bianchi, Filippo Maria
Bilde av Bianchi, Filippo Maria
Associate Professor Institutt for matematikk og statistikk filippo.m.bianchi@uit.no +4777625176 Her finner du meg

Filippo Maria Bianchi

Stillingsbeskrivelse

My research interests lie at the intersection between machine learning, dynamical systems, and complex networks. The main areas where I apply my research are energy analytics and remote sensing.

More info at:

  • Karoline Ingebrigtsen, Filippo Maria Bianchi, Sigurd Bakkejord, Inga Setså Holmstrand, Matteo Chiesa :
    Identifying conditions leading to power quality events in Arctic Norway: Feature selection
    Applied Energy 2024 DOI
  • Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi :
    Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
    Proceedings of Machine Learning Research (PMLR) 2024 ARKIV / DOI
  • Filippo Maria Bianchi, Veronica Lachi :
    The expressive power of pooling in Graph Neural Networks
    Advances in Neural Information Processing Systems 2023 ARKIV / FULLTEKST / DOI
  • Michele Guerra, Indro Spinelli, Simone Scardapane, Filippo Maria Bianchi :
    Explainability in subgraphs-enhanced Graph Neural Networks
    Proceedings of the Northern Lights Deep Learning Workshop 23. januar 2023 ARKIV / DOI
  • Jonas Berg Hansen, Filippo Maria Bianchi :
    Total Variation Graph Neural Networks
    Proceedings of Machine Learning Research (PMLR) 2023 ARKIV / SAMMENDRAG
  • Filippo Maria Bianchi :
    Simplifying Clustering with Graph Neural Networks
    Proceedings of the Northern Lights Deep Learning Workshop 23. januar 2023 FULLTEKST / ARKIV / DOI
  • Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi :
    Scalable Spatiotemporal Graph Neural Networks
    Proceedings of the AAAI Conference on Artificial Intelligence 2023 FULLTEKST / ARKIV / DOI
  • Odin Foldvik Eikeland, Colin C. Kelsall, Kyle Buznitsky, Shomik Verma, Filippo Maria Bianchi, Matteo Chiesa m.fl.:
    Power availability of PV plus thermal batteries in real-world electric power grids
    Applied Energy 2023 ARKIV / DOI
  • Michele Guerra, Simone Scardapane, Filippo Maria Bianchi :
    Probabilistic Load Forecasting With Reservoir Computing
    IEEE Access 15. desember 2023 ARKIV / DOI
  • Odin Foldvik Eikeland, Filippo Maria Bianchi, Inga Setså Holmstrand, Sigurd Bakkejord, Sergio Santos Hernandez, Matteo Chiesa :
    Uncovering Contributing Factors to Interruptions in the Power Grid: An Arctic Case
    Energies 03. januar 2022 ARKIV / DOI
  • 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
    Energy Conversion and Management: X 2022 ARKIV / DOI
  • Jonas Berg Hansen, Stian Normann Anfinsen, Filippo Maria Bianchi :
    Power Flow Balancing With Decentralized Graph Neural Networks
    IEEE Transactions on Power Systems 01. august 2022 ARKIV / DOI
  • Iver Martinsen, Alf Harbitz, Filippo Maria Bianchi :
    Age prediction by deep learning applied to Greenland halibut (Reinhardtius hippoglossoides) otolith images
    PLOS ONE 2022 ARKIV / DOI
  • Daniele Grattarola, Daniele Zambon, Filippo Maria Bianchi, Cesare Alippi :
    Understanding Pooling in Graph Neural Networks
    IEEE Transactions on Neural Networks and Learning Systems 21. juli 2022 ARKIV / DOI
  • Jakob Grahn, Filippo Maria Bianchi :
    Recognition of Polar Lows in Sentinel-1 SAR Images With Deep Learning
    IEEE Transactions on Geoscience and Remote Sensing 06. september 2022 ARKIV / DOI
  • Vilde Jensen, Filippo Maria Bianchi, Stian Normann Anfinsen :
    Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting
    IEEE Transactions on Neural Networks and Learning Systems 2022 ARKIV / DOI
  • Luigi Tommaso Luppino, Mads Adrian Hansen, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Robert Jenssen m.fl.:
    Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
    IEEE Transactions on Neural Networks and Learning Systems 12. mai 2022 DOI
  • Anne Gerd Imenes, Nadia Saad Noori, Ole Andreas Nesvåg Uthaug, Robert Kröni, Filippo Maria Bianchi, Nabil Belbachir :
    A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites
    IEEE conference proceedings 2021 FULLTEKST / DOI
  • 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
    IEEE conference proceedings 2021 DOI
  • Filippo Maria Bianchi, Claudio Gallicchio, Alessio Micheli :
    Pyramidal Reservoir Graph Neural Network
    Neurocomputing 2021 DOI
  • 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 2021 ARKIV / DOI
  • Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi :
    Graph Neural Networks With Convolutional ARMA Filters
    IEEE Transactions on Pattern Analysis and Machine Intelligence 26. januar 2021 DOI
  • Karl Øyvind Mikalsen, Cristina Soguero Ruiz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen :
    Time series cluster kernels to exploit informative missingness and incomplete label information
    Pattern Recognition 2021 ARKIV / DOI
  • Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Sebastiano Bruno Serpico, Robert Jenssen m.fl.:
    Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection
    IEEE Transactions on Geoscience and Remote Sensing 2021 ARKIV / DOI
  • Odin Foldvik Eikeland, Filippo Maria Bianchi, Matteo Chiesa, Harry Apostoleris, Morten Hansen, Yu-Cheng Chiou :
    Predicting Energy Demand in Semi-Remote Arctic Locations
    Energies 2021 ARKIV / DOI
  • Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen :
    Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series
    IEEE Transactions on Neural Networks and Learning Systems 2021 ARKIV / DOI
  • Martin Wibe Rypdal, Kristoffer Rypdal, Ola Løvsletten, Sigrunn Holbek Sørbye, Elinor Ytterstad, Filippo Maria 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 (IJERPH) 2021 ARKIV / DOI
  • Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi :
    Spectral Clustering with Graph Neural Networks for Graph Pooling
    Proceedings of Machine Learning Research (PMLR) 2020
  • Filippo Maria Bianchi, Martine Espeseth, Njål Trygve Borch :
    Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning
    Remote Sensing 2020 ARKIV / DOI
  • Changkyu Choi, Filippo Maria Bianchi, Michael Kampffmeyer, Robert Jenssen :
    Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks
    Proceedings of the Northern Lights Deep Learning Workshop 2020 ARKIV / DOI
  • Filippo Maria Bianchi, Jakob Grahn, Markus Eckerstorfer, Eirik Malnes, Hannah Vickers :
    Snow avalanche segmentation in SAR images with Fully Convolutional Neural Networks
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2020 DOI
  • Kristoffer Rypdal, Filippo Maria Bianchi, Martin Rypdal :
    Intervention Fatigue is the Primary Cause of Strong Secondary Waves in the COVID-19 Pandemic
    International Journal of Environmental Research and Public Health (IJERPH) 2020 DOI
  • Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi :
    Hierarchical Representation Learning in Graph Neural Networks With Node Decimation Pooling
    IEEE Transactions on Neural Networks and Learning Systems 2020 ARKIV / DOI
  • Michael C. Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt Børre Salberg, Robert Jenssen :
    Deep divergence-based approach to clustering
    Neural Networks 2019 ARKIV / DOI
  • Karl Øyvind Mikalsen, Cristina Soguero-Ruiz, Filippo Maria Bianchi, Robert Jenssen :
    Noisy multi-label semi-supervised dimensionality reduction
    Pattern Recognition 2019 ARKIV / DOI
  • Luigi Tommaso Luppino, Filippo Maria Bianchi, Gabriele Moser, Stian Normann Anfinsen :
    Unsupervised Image Regression for Heterogeneous Change Detection
    IEEE Transactions on Geoscience and Remote Sensing 14. august 2019 ARKIV / FULLTEKST / DOI
  • Filippo Maria Bianchi, Lorenzo Livi, Karl Øyvind Mikalsen, Michael C. Kampffmeyer, Robert Jenssen :
    Learning representations of multivariate time series with missing data
    Pattern Recognition 2019 ARKIV / DOI
  • Alessandro Cinti, Filippo Maria Bianchi, Alessio Martino, Antonello Rizzi :
    A Novel Algorithm for Online Inexact String Matching and its FPGA Implementation
    Cognitive Computation 2019 ARKIV / DOI
  • Ralph Kube, Filippo Maria Bianchi, Dan Brunner, Brian LaBombard :
    Outlier classification using autoencoders: Application for fluctuation driven flows in fusion plasmas
    Review of Scientific Instruments 2019 ARKIV / DOI
  • Filippo Maria Bianchi :
    Learning representations of multivariate time series with missing data
    Pattern Recognition 2019 DOI
  • Davide Bacciu, Filippo Maria Bianchi, Benjamin Paassen, Cesare Alippi :
    Deep learning for graphs
    2018
  • Michael C. Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi :
    The deep kernelized autoencoder
    Applied Soft Computing 2018 ARKIV / DOI
  • Filippo Maria Bianchi, Karl Øyvind Mikalsen, Robert Jenssen :
    Learning compressed representations of blood samples time series with missing data
    2018 DOI
  • Luigi Tommaso Luppino, Filippo Maria Bianchi, Gabriele Moser, Stian Normann Anfinsen :
    Remote sensing image regression for heterogeneous change detection
    IEEE Signal Processing Society 2018 FULLTEKST / ARKIV / DOI
  • Benjamin Ricaud, Filippo Maria Bianchi :
    Learning on Graphs (LoG) meetup in Tromsø
    2023
  • Benjamin Ricaud, Volodymyr Miz, Filippo Maria Bianchi, Nicolas Aspert :
    Introduction to Graph Machine Learning
    2022 DATA
  • Anne Gerd Imenes, Nadia Saad Noori, Ole Andreas Nesvåg Uthaug, Robert Kröni, Filippo Maria Bianchi, Nabil Belbachir :
    A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites
    2021 FULLTEKST
  • Nadia Saad Noori, Tor Inge Waag, Filippo Maria Bianchi :
    Condition Monitoring System for Internal Blowout Prevention (IBOP) in Top Drive Assembly System using Discrete Event Systems and Deep Learning Approaches
    2020 ARKIV
  • Changkyu Choi, Filippo Maria Bianchi, Michael Kampffmeyer, Robert Jenssen :
    Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks
    2020 ARKIV / FULLTEKST
  • Filippo Maria Bianchi, Ponnuthurai Nagaratnam Suganthan :
    Non-iterative Learning Approaches and Their Applications
    Cognitive Computation 2020 ARKIV / DOI

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    Forskningsinteresser

    Machine learning; Graph theory; Time series analysis

    ResearchGate
    ORCID: https://orcid.org/0000-0002-7145-3846

    Medlem i forskningsgruppe

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