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Bilde av Bianchi, Filippo Maria
Bilde av Bianchi, Filippo Maria
Institutt for matematikk og statistikk filippo.m.bianchi@uit.no +4777625176 Tromsø You can find me here

Filippo Maria Bianchi

Job description

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

More info at:

  • Jonas Berg, Andrea, Filippo Maria :
    On Time Series Clustering with Graph Neural Networks
    Transactions on Machine Learning Research (TMLR) 31. août 2025 DOI
  • Andrea, Alexander, Danilo, Cesare, Filippo Maria :
    Relational Conformal Prediction for Correlated Time Series
    2025 42th International Conference on Machine Learning 01. mai 2025 DOI
  • Carlo, Filippo Maria :
    MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks
    International Conference on Learning Representations 2025 ARKIV
  • Jakob, Filippo Maria, Karsten, Eirik :
    Data-driven avalanche forecasting using weather and satellite data
    International Snow Science Workshops (ISSW) Proceedings 2024 ARKIV
  • Ivan, Cesare, Filippo Maria :
    Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
    Proceedings of Machine Learning Research (PMLR) 2024 DOI / ARKIV / FULLTEKST
  • Karoline, Filippo Maria, Sigurd, Inga Setså, Matteo :
    Identifying conditions leading to power quality events in Arctic Norway: Feature selection
    Applied Energy 2024 DOI / ARKIV
  • Andrea, Ivan, Filippo Maria, Cesare :
    Scalable Spatiotemporal Graph Neural Networks
    Proceedings of the AAAI Conference on Artificial Intelligence 2023 DOI / ARKIV
  • Filippo Maria :
    Simplifying Clustering with Graph Neural Networks
    Proceedings of the Northern Lights Deep Learning Workshop 23. janvier 2023 DOI / ARKIV
  • Filippo Maria, Veronica :
    The expressive power of pooling in Graph Neural Networks
    Advances in Neural Information Processing Systems 2023 DOI / ARKIV / FULLTEKST
  • Odin Foldvik, Colin C., Kyle, Shomik, Filippo Maria, Matteo et al.:
    Power availability of PV plus thermal batteries in real-world electric power grids
    Applied Energy 2023 DOI / ARKIV
  • Michele, Indro, Simone, Filippo Maria :
    Explainability in subgraphs-enhanced Graph Neural Networks
    Proceedings of the Northern Lights Deep Learning Workshop 23. janvier 2023 DOI / ARKIV
  • Michele, Simone, Filippo Maria :
    Probabilistic Load Forecasting With Reservoir Computing
    IEEE Access 15. décembre 2023 DOI / ARKIV
  • Jonas Berg, Filippo Maria :
    Total Variation Graph Neural Networks
    Proceedings of Machine Learning Research (PMLR) 2023 ARKIV
  • Jonas Berg, Stian Normann, Filippo Maria :
    Power Flow Balancing With Decentralized Graph Neural Networks
    IEEE Transactions on Power Systems 01. août 2022 DOI / ARKIV
  • Odin Foldvik, Filippo Maria, Inga Setså, Sigurd, Sergio Santos, Matteo :
    Uncovering Contributing Factors to Interruptions in the Power Grid: An Arctic Case
    Energies 03. janvier 2022 DOI / ARKIV
  • Luigi Tommaso, Mads Adrian, Michael, Filippo Maria, Gabriele, Robert et al.:
    Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
    IEEE Transactions on Neural Networks and Learning Systems 12. mai 2022 DOI
  • Odin Foldvik, Finn Dag, Tom Eirik, Matteo, Filippo Maria :
    Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case
    Energy Conversion and Management: X 2022 DOI / ARKIV
  • Daniele, Daniele, Filippo Maria, Cesare :
    Understanding Pooling in Graph Neural Networks
    IEEE Transactions on Neural Networks and Learning Systems 21. juillet 2022 DOI / ARKIV
  • Jakob, Filippo Maria :
    Recognition of Polar Lows in Sentinel-1 SAR Images With Deep Learning
    IEEE Transactions on Geoscience and Remote Sensing 06. septembre 2022 DOI / ARKIV
  • Vilde, Filippo Maria, Stian Normann :
    Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting
    IEEE Transactions on Neural Networks and Learning Systems 2022 DOI / ARKIV
  • Iver, Alf, Filippo Maria :
    Age prediction by deep learning applied to Greenland halibut (Reinhardtius hippoglossoides) otolith images
    PLOS ONE 2022 DOI / ARKIV
  • Anne Gerd, Nadia Saad, Ole Andreas Nesvåg, Robert, Filippo Maria, Nabil :
    A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites
    2021 DOI / FULLTEKST
  • Filippo Maria, Daniele, Lorenzo, Cesare :
    Graph Neural Networks With Convolutional ARMA Filters
    IEEE Transactions on Pattern Analysis and Machine Intelligence 26. janvier 2021 DOI
  • Karl Øyvind, Cristina Soguero, Filippo Maria, Arthur, Robert :
    Time series cluster kernels to exploit informative missingness and incomplete label information
    Pattern Recognition 2021 DOI / ARKIV
  • Filippo Maria, Simone, Sigurd, Robert :
    Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series
    IEEE Transactions on Neural Networks and Learning Systems 2021 DOI / ARKIV
  • Luigi Tommaso, Michael, Filippo Maria, Gabriele, Sebastiano Bruno, Robert et al.:
    Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection
    IEEE Transactions on Geoscience and Remote Sensing 2021 DOI / ARKIV
  • Odin Foldvik, Inga Setså, Sigurd, Matteo, Filippo Maria :
    Detecting and Interpreting Faults in Vulnerable Power Grids With Machine Learning
    IEEE Access 2021 DOI / ARKIV
  • Huamin, Filippo Maria, Jingyue, Rasmus L., Robert, Stian Normann :
    Towards Applicability: A Comparative Study on Non-Intrusive Load Monitoring Algorithms
    2021 DOI
  • Martin Wibe, Kristoffer, Ola, Sigrunn Holbek, Elinor, Filippo Maria :
    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 DOI / ARKIV
  • Filippo Maria, Claudio, Alessio :
    Pyramidal Reservoir Graph Neural Network
    Neurocomputing 2021 DOI
  • Odin Foldvik, Filippo Maria, Matteo, Harry, Morten, Yu-Cheng :
    Predicting Energy Demand in Semi-Remote Arctic Locations
    Energies 2021 DOI / ARKIV
  • Filippo Maria, Daniele, Cesare :
    Spectral Clustering with Graph Neural Networks for Graph Pooling
    Proceedings of Machine Learning Research (PMLR) 2020
  • Filippo Maria, Daniele, Lorenzo, Cesare :
    Hierarchical Representation Learning in Graph Neural Networks With Node Decimation Pooling
    IEEE Transactions on Neural Networks and Learning Systems 2020 DOI / ARKIV
  • Filippo Maria, Jakob, Markus, Eirik, Hannah :
    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, Filippo Maria, Martin :
    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, Martine, Njål Trygve :
    Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning
    Remote Sensing 2020 DOI / ARKIV
  • Changkyu, Filippo Maria, Michael, Robert :
    Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks
    Proceedings of the Northern Lights Deep Learning Workshop 2020 DOI / ARKIV
  • Alessandro, Filippo Maria, Alessio, Antonello :
    A Novel Algorithm for Online Inexact String Matching and its FPGA Implementation
    Cognitive Computation 2019 DOI / ARKIV
  • Filippo Maria :
    Learning representations of multivariate time series with missing data
    Pattern Recognition 2019 DOI
  • Karl Øyvind, Cristina, Filippo Maria, Robert :
    Noisy multi-label semi-supervised dimensionality reduction
    Pattern Recognition 2019 DOI / ARKIV
  • Michael C., Sigurd, Filippo Maria, Lorenzo, Arnt Børre, Robert :
    Deep divergence-based approach to clustering
    Neural Networks 2019 DOI / ARKIV
  • Ralph, Filippo Maria, Dan, Brian :
    Outlier classification using autoencoders: Application for fluctuation driven flows in fusion plasmas
    Review of Scientific Instruments 2019 DOI / ARKIV
  • Filippo Maria, Eirik :
    A Bird's Eye View on Snow Avalanches
    2025
  • Filippo Maria :
    Pooling in Graph Neural Networks
    2024 DOI
  • Benjamin, Filippo Maria :
    Learning on Graphs (LoG) meetup in Tromsø
    2023
  • Benjamin, Volodymyr, Filippo Maria, Nicolas :
    Introduction to Graph Machine Learning
    2022
  • Anne Gerd, Nadia Saad, Ole Andreas Nesvåg, Robert, Filippo Maria, Nabil :
    A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites
    2021 FULLTEKST
  • Changkyu, Filippo Maria, Michael, Robert :
    Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks
    2020 ARKIV / FULLTEKST
  • Filippo Maria, Ponnuthurai Nagaratnam :
    Non-iterative Learning Approaches and Their Applications
    Cognitive Computation 2020 DOI / ARKIV
  • Nadia Saad, Tor Inge, Filippo Maria :
    Condition Monitoring System for Internal Blowout Prevention (IBOP) in Top Drive Assembly System using Discrete Event Systems and Deep Learning Approaches
    2020 ARKIV

    • The 50 latest publications is shown on this page. See all publications in Cristin here →

    Research interests

    Machine learning; Graph theory; Time series analysis

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

    Member of research group

    ARC   English content
    Forskningsparken 1 B490


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