Work in progress and current projects

► Unpublished works

•  Solym M. Manou-Abi (2017).  Rate of convergence to stable law using zolotarev distance: technical report. https://doi.org/10.48550/arXiv.1712.09294

• Solym M. Manou-Abi and Julien Balicchi (2020).  Analysis of the COVID-19 epidemic in french overseas department Mayotte based on a modified deterministic and stochastic SEIR model. MedRxiv, 2020-04 

► PAPERS IN PROGRESS

• Solym Manou-Abi and al. Statistical learning from stable distributions :  regressions models  and quantile statistics with application to epidemiological and financial real datasets.  In progress

• Solym M. Manou-Abi. Bayesian inference for  discretely observed stable driven stochastic models with application. In progress.

• Solym M. Manou-Abi. Stable driven stochastic models: ergodic and mixing properties under Wasserstein and total variation distances. In progress.

• Solym M. Manou-Abi. Stein Method for Stable Laws and Machine Learning: A new Framework for robust Learning with Heavy-Tailed Data.

• Solym M. Manou-Abi and Stefana Taberra Tsillefa. Physics Informed Deep Learning (PINNs)  with stable driven SDE models. In progress

• Fridolin Melon and Solym Manou-Abi. Parameter estimation for the R(p,q)-binomial probability distribution. In progress

• Guilherme Hilário Monteiro, Solym M. Manou-Abi, Bedreddine Ainseba and Stefanella Boatto. Modeling Weather-Driven Dynamics of Dengue Mosquitoes  with Sparse Capture Data in Mayotte. In progress.

• Essoham Ali,  Solym M. Manou-Abi, Yousri Slaoui and Julien Balicchi.  Modeling contact patterns in the island of Mayotte using count data regression with multicollinearity and Power divergence estimators with random effects. In progress.

► PROJECTS  (with financial support)

• Python and R Library project for parameter estimation of stable laws and for simulations of stable driven SDEs.

• Anomalous Diffusions for Image Generation (AnDIG): Investigation of anomalous diffusions driven by stable processes for the synthesis of non-standardly distributed images.

• Statistical estimation with Partial Differential Equation model with real mosquito data and Physics Informed Neural Networks (PINNs)

• Stein Method for Stable Laws and Machine Learning: A new Framework for robust Learning with Heavy-Tailed Data.