Scholar
Ségolène Martin
Google Scholar ID: EaJ0WlMAAAAJ
Postdoc, TU Berlin
Citations & Impact
Citations
99
H-index
4
i10-index
4
Publications
15
Co-authors
0
Publications
Resume
Background
- Research interests lie at the intersection of large-scale continuous optimization, inverse problems in imaging, generative learning, and image classification.
- Current research focuses on optimization and generative learning with applications to image processing and computer vision.
- Key methodological interests include Majoration-Minimization, proximal algorithms, subspace acceleration, and convergence theory.
- Works on image restoration and reconstruction within the Bayesian framework, and generative models such as flow-based models, GANs, and VAEs.
- Explores clustering and few-shot optimization-based methods, unbalanced few-shot learning, transductive learning, and text-vision models.