Advestis
A Brief Overview of Methods to Explain AI (XAI)
V. Margot. Towards Data Science, November, 26th 2021.
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Research
Advestis has been developing and operating ML algorithms in commercial production since 2013.
Since 2014, Advestis has grown an expertise in ESG features engineering
and solving complex problems involving them.
Explore our Research below
Rechercher
Advestis
- 25 nov. 2021
A New Method to Compare the Interpretability of Rule-Based Algorithms
V. Margot and G. Luta. MDPI AI 2021.
Advestis
- 27 oct. 2021
An original method to combine regression estimators in Python.
V. Margot, Towards Data Science, October 27th, 2021.
Advestis
- 22 juin 2021
Sharp estimates for the integrated density of states in Anderson tight-binding models
Perceval Desforges, Svitlana Mayboroda, Shiwen Zhang, Guy David, Douglas N. Arnold, Wei Wang, and Marcel Filoche. Phys. Rev. A, June 2021.
Advestis
- 31 mai 2021
Online Bayesian inference for multiple changepoints and risk assessment
O. Sorba and C. Geissler. Advestis Working Paper, May 2021.
Advestis
- 22 mars 2021
Speed Cubing for Machine Learning - Episode 3
N. Morizet, Towards Data Science, March 22nd, 2021.
Advestis
- 19 mars 2021
TransparentPath: A Python package to manage paths on Google Cloud Storage
Are you used to pathlib’s Path objects and frustrated when using GCSFileSystem objects ?
The TransparentPath package is made for you.
Advestis
- 17 févr. 2021
How to deal with overlapping rules?
V. Margot, Towards Data Science, February 17th, 2021.
Advestis
- 17 févr. 2021
Applying separative non-negative matrix factorization to extra-financial data
P. Fogel, C. Geissler, P. Cotte and G. Luta. Bankers Markets & Investors: an academic & professional review, Groupe Banque, In press. Feb21.
Advestis
- 26 janv. 2021
Consistent Regression using Data-Dependent Coverings
V. Margot, JP. Baudry, F. Guilloux and O. Wintenberger. Electronic Journal of Statistics 15(1)1743 - 1782, 2021.
Advestis
- 18 déc. 2020
How to choose the best model?
V. Margot, Towards Data Science, December 18th, 2020.
Advestis
- 26 nov. 2020
Accelerating Pandas concatenation
P. Cotte, Towards Data Science, November 26th, 2020.
Advestis
- 21 nov. 2020
How to measure interpretability?
V. Margot, Towards Data Science, November 21st, 2020.
Advestis
- 20 nov. 2020
Speed Cubing for Machine Learning - Episode 2
N. Morizet, Towards Data Science, November 20th, 2020.
Advestis
- 2 oct. 2020
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
- 23 sept. 2020
A rigorous method to compare interpretability of rule-based algorithms
V. Margot, Preprint, 2020.
Advestis
- 15 sept. 2020
Speed Cubing for Machine Learning - Episode 1
N. Morizet, Towards Data Science, September 15th, 2020.
Advestis
- 15 juil. 2020
Introduction to Generative Adversarial Networks
N. Morizet, Advestis Tech Report, July 2020.
Advestis
- 27 avr. 2020
A self-learning and interpretable investment strategy based on extra-financial data
C. Geissler, V. Margot, Chaire DAMI, September 2020.
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