Advestis
A Pilot Study on the Use of Generative Adversarial Networks for Data Augmentation of Time Series
N. Morizet, M. Rizzato, D. Grimbert and G. Luta. Brief Report, MDPI AI Special Issue "Feature Papers for AI", September 26th 2022.
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
- 24 sept.
An entry point to clustering methods
W. Maréchal. Medium, September 24th 2022.
Advestis
- 13 juil.
Generative Adversarial Networks Applied to Synthetic Financial Scenarios
C. Geissler, N. Morizet, M. Rizzato and J. Wallart. Preprint, July 2022.
Advestis
- 11 juil.
Stress testing electrical grids: Generative Adversarial Networks for load scenario generation
M. Rizzato, N. Morizet, W. Maréchal and C. Geissler. "Elsevier Energy and AI" 9 (2022).
Advestis
- 19 mai
Relevance of Optimized Low-Scale Green H2 Systems in a French Context: Two Case Studies
T. Gronier, W. Maréchal, S. Gibout and C. Geissler. MDPI Energies, 19 May 2022.
Advestis
- 10 mai
Quadratic Optimization with Constraints in Python using CVXOPT
P. Desforges. Towards Data Science. May, 10th 2022.
Advestis
- 21 avr.
Do You Know the Logical Analysis of Data Methodology (LAD)?
V. Margot. Towards Data Science, April 21st.
Advestis
- 25 mars
Mode of Neonatal Delivery Influences the Nutrient Composition of Human Milk
Samuel TM, Thielecke F, Lavalle L, Chen C, Fogel P et al. Front. Nutr. 9:8344394, 2022.
Advestis
- 25 mars
A2Sign: Agnostic Algorithms for Signatures
G. Boldina, P. Fogel, C. Rocher, C. Bettembourg, G. Luta and F. Augé. Bioinformatics, Volume 38, Issue 4, Pages 1015-1021, 15 February 2022.
Advestis
- 9 mars
Extremely expensive likelihoods - A variational-Bayes solution for precision cosmology
M. Rizzato and E. Sellentin. arXiv Preprint, submitted to MNRAS, March 9th, 2022.
Advestis
- 1 mars
Making use of supercomputers in financial machine learning
P. Cotte, P. Lagier, V. Margot and C. Geissler. arXiv Preprint, March, 1st 2022.
Advestis
- 11 févr.
Model Pruning in Deep Neural Networks Using the Tensorflow API
P. Desforges. Towards Data Science. February, 11th 2022.
Advestis
- 4 janv.
Four interpretable algorithms that you should use in 2022
V. Margot. Towards Data Science. January, 4th 2022.
Advestis
- 26 nov. 2021
A Brief Overview of Methods to Explain AI (XAI)
V. Margot. Towards Data Science, November, 26th 2021.
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.