News

I have an exciting post-doc position in computational lightfield microscopy. If interested you can apply here.

• Invertible Neural Networks and Their Applications, IEEE SPS Webinar, July 2024 (see also related papers link1 and link2.)
  
• Model-Based Deep Learning for Inverse Problems, I-X Breaking Topics in AI conference, Imperial I-X, November 2023 (video);
• Timing is everything: model-based and learning-based reconstruction methods for event-driven cameras,      Edinburgh, May 2023 (see also related papers link1 and link2.)
  
• Sparsity and Deep Neural Networks: a Match Made in Heaven, UCL, UK, February 2022
• New Sparse Sampling Methods: Time-based Sampling and Sampling along Trajectories One World Signal       Processing Seminars, December 2021

• Di You and P.L. Dragotti,"INDIGO+: A Unified INN-Guided Probabilistic Diffusion Algorithm for Blind and Non-Blind Image Restoration", IEEE Journal of Selected Topics in Signal Processing, 2024 (open access). GitHub link to code (here)
• H. Verinaz et al. "Physics-based Deep Learning for Imaging Neuronal Activity via Two-photon and Light-field Microscopy", IEEE Trans. on Computational Imaging, 2023, (Biorxiv version here)
• Y. Su et al.A Fast Automatic Method for Deconvoluting Macro X-ray Fluorescence Data Collected from Easel Painting", IEEE Transactions on Computational Imaging, 2023.(code here).
  
• J.J. Huang and P.L. Dragotti,  "WINNet: Wavelet-inspired invertible network for image denoising", IEEE Transactions on Image Processing", 2022 (open access), GitHub link to code
  
• P. Song et al."Light-field Microscopy for optical imaging of neural activity: when model-based methods meet data-driven approaches" IEEE Signal Processing Magazine, vol 39 March 2022 (arxiv version here).
• Y. Su et al. "When de Prony met Leonardo: An automatic algorithm for chemical element extraction from macro X-Ray Fluorescence Data", IEEE Transactions on Computational Imaging, vol.7, 2021.
• X.Deng and P.L. Dragotti, Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.43 (10), October 2021. GitHub link to code
  

• "AI may have a thing or two to learn from our imperfect brains", Forbes
• We uncover forgotten figures beneath one of Leonardo's paintings
• An article from Le Temps, Geneva
• Video from NewScientist.
• Wavelet Footprints on IEEE Spectrum