top of page
Research
Advestis part of R&D Forvis Mazars has been developing and operating ML algorithms
in commercial production since 2013.
Explore our Research below
Rechercher
Interpretable Algorithms for Regression: Theory and Applications
V. Margot, PhD Thesis, Sorbonne Université, October 2nd, 2020.
Advestis
1 oct. 2020
Using Non-negative matrix factorization to classify companies
C. Geissler, Towards Data Science, October 1st, 2020.
Advestis
1 oct. 2020
A rigorous method to compare interpretability of rule-based algorithms
V. Margot, Preprint, 2020.
Advestis
23 sept. 2020
Speed Cubing for Machine Learning - Episode 1
N. Morizet, Towards Data Science, September 15th, 2020.
Advestis
15 sept. 2020
Introduction to Generative Adversarial Networks
N. Morizet, Advestis Tech Report, July 2020.
Advestis
15 juil. 2020
A self-learning and interpretable investment strategy based on extra-financial data
C. Geissler, V. Margot, Chaire DAMI, September 2020.
Advestis
27 avr. 2020
Non-Gaussian cosmology: theoretical and statistical challenges for model galaxy surveys
M. Rizzato. PhD Thesis, 26th September 2019, Institut d'Astrophysique de Paris.
Advestis
25 sept. 2019
Apprentissage supervisé pour la sélection d'actions
C. Geissler, V. Margot, Chaire DAMI, March 27th 2019.
Advestis
27 mars 2019
ESG investments: Filtering versus Machine Learning approaches
C. Geissler, V. Margot et al. The 7th Public Investors Conference, October 22nd, 2018, Rome, Italy.
Advestis
22 oct. 2018
Rule Induction Partitioning Estimator
V. Margot, JP. Baudry, F. Guilloux and O. Wintenberger. MLDM2018, LNCS, vol 10935. Springer.
Advestis
11 juil. 2018
AdLearn : Un Algorithme d'Apprentissage Interprétable
V. Margot, O. Wintenberger, JP. Baudry, F. Guilloux and C. Geissler. 49èmes Journées de Statistiques, 2017.
Advestis
28 mai 2017
Rule Extraction from Large Numerical Datasets: Construction of ESG Signals
C. Geissler, Advestis and Sustainalytics, December 2016.
Advestis
1 déc. 2016
bottom of page