Giacomo Meanti
Scholar

Giacomo Meanti

Google Scholar ID: g1n-MOEAAAAJ
Istituto Italiano di Tecnologia
Machine LearningKernel MethodsLarge Scale Learning
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Citations & Impact
All-time
Citations
1,027
 
H-index
7
 
i10-index
6
 
Publications
13
 
Co-authors
0
 
Contact
CVOpen ↗GitHubOpen ↗
Publications
3 items
kooplearn: A Scikit-Learn Compatible Library of Algorithms for Evolution Operator Learning
2025
Cited
0
MAP Estimation with Denoisers: Convergence Rates and Guarantees
2025
Cited
0
Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
2025
Cited
0
Resume (English only)
Academic Achievements
  • Paper 'DDM4IP' accepted at ICCV 2025; presented workshop paper on finetuning foundation models for molecular dynamics using kernels; paper on efficient Koopman operator learning with Nyström approximation available on ArXiv; completed PhD thesis titled 'Large Scale Kernel Methods for Fun and Profit'.
Research Experience
  • Currently a PostDoc at INRIA Grenoble in the Thoth team, supervised by Julien Mairal. Presented K-Planes algorithm at CVPR and research on efficient Koopman operator learning at NeurIPS.
Education
  • Completed PhD at the University of Genova, supervised by Lorenzo Rosasco.
Background
  • Research interests include inverse problems for imaging, developing efficient algorithms for shallow learning, and applying kernel methods and shallow learning algorithms to scientific applications.
Miscellany
  • Contact email: giacomo [dot] meanti [at] gmail [dot] com
Co-authors
0 total
Co-authors: 0 (list not available)