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

Clinical Assessment of Puressentiel® Muscles and Joints Gel Aromatherapy in the Management of Osteoarthritis-Related Knee Pain

Advestis

il y a 4 jours

Clinical Assessment of Puressentiel® Muscles and Joints Gel Aromatherapy in the Management of Osteoarthritis-Related Knee Pain

P. Fogel, N. Barizien, P. Capron, T. Mamou, F. Louni, and R. Krzentowski. In "MDPI Healthcare" 13(2), January 2025.

Integrated sources model: A new space-learning model for heterogeneous multi-view data reduction, visualization, and clustering

Advestis

24 juil. 2024

Integrated sources model: A new space-learning model for heterogeneous multi-view data reduction, visualization, and clustering

P. Fogel, C. Geissler, F. Augé, G. Boldina, and George Luta. In "Artificial Intelligence in Health", July 2024.

Applying non-negative tensor factorization to centered data

Advestis

17 mai 2024

Applying non-negative tensor factorization to centered data

P. Fogel, C. Geissler, H. J. Von Mettenheim, and G. Luta. BMI, Vol. 174, n°3 (2023).

Impact of surgical approach on 90-day mortality after lung resection for non-small cell lung cancer in high-risk operable patients

Advestis

6 févr. 2024

Impact of surgical approach on 90-day mortality after lung resection for non-small cell lung cancer in high-risk operable patients

H. Etienne, V. Margot, P. Mordant et al. In "ERJ Open Research", Vol. 10, Issue 1, 2024.

An adaptative approach for estimating the remaining useful life of a heavy-duty fuel cell vehicle

Advestis

2 févr. 2024

An adaptative approach for estimating the remaining useful life of a heavy-duty fuel cell vehicle

N. Morizet, P. Desforges, C. Geissler, E. Pahon, S. Jemei and D. Hissel. In "Elsevier Journal of Power Sources", Vol. 597, 30 March 2024.

Using Federated Learning for Collaborative Intrusion Detection Systems

Advestis

12 déc. 2023

Using Federated Learning for Collaborative Intrusion Detection Systems

M. Rizzato, Y. Laarouchi and C. Geissler. Journal of Systemics, Cybernetics and Informatics, 21(3), 29-36 (2023).

On Rank Selection in Non-Negative Matrix Factorization using Concordance

Advestis

10 nov. 2023

On Rank Selection in Non-Negative Matrix Factorization using Concordance

P. Fogel, C. Geissler, N. Morizet and G. Luta. "Special Issue Advances in Applied Probability and Statistical Inference", MDPI 2023.

Preventing Acute Limb Ischemia during VA-ECMO—In Silico Analysis of Physical Parameters

Advestis

19 oct. 2023

Preventing Acute Limb Ischemia during VA-ECMO—In Silico Analysis of Physical Parameters

T. Brockaert, I. Ferreira, A. Laplante, P. Fogel, D. Grimbert and P. Mordant. Published in MDPI Journal of Clinical Medecine, 09/19/23.

Advestis

12 sept. 2023

Using Federated Learning for collaborative intrusion detection systems

M. Rizzato, Y. Laarouchi and C. Geissler. Proceedings of The 27th WMSCI, September 13th, 2023.

ChatGPT: Usages, impacts & recommandations

Advestis

7 sept. 2023

ChatGPT: Usages, impacts & recommandations

N. Morizet, D. Grimber avec le Hub FranceIA. Dossier paru dans le Journal ActuIA n°12, pp. 25-31, Juillet-Septembre 2023.

Time to market reduction for hydrogen fuel cell stacks using Generative Adversarial Networks

Advestis

14 juin 2023

Time to market reduction for hydrogen fuel cell stacks using Generative Adversarial Networks

N. Morizet, P. Desforges, C. Geissler, E. Pahon, S. Jemei and D. Hissel. In "Elsevier Journal of Power Sources", 30 September 2023.

Generative Adversarial Networks applied to synthetic financial scenarios generation

Advestis

21 mai 2023

Generative Adversarial Networks applied to synthetic financial scenarios generation

M. Rizzato, J. Wallart, C. Geissler, N. Morizet and N. Boumlaik. In "Elsevier Physica A", 18 May 2023.

CHAT GPT : USAGES, IMPACTS ET RECOMMANDATIONS

Advestis

1 mai 2023

CHAT GPT : USAGES, IMPACTS ET RECOMMANDATIONS

Hub FranceIA, Advestis et al. Note de synthèse. Mai 2023.

Analysis of the Relevance of Sentiment Data for the Prediction of ERs in a Multi-Asset Framework

Advestis

15 févr. 2023

Analysis of the Relevance of Sentiment Data for the Prediction of ERs in a Multi-Asset Framework

P. Desforges, C. Geissler and F. Liu. Journal of Forecasting, 15 February 2023.

Usage of GAMS-Based Digital Twins and Clustering to Improve Energetic Systems Control

Advestis

22 déc. 2022

Usage of GAMS-Based Digital Twins and Clustering to Improve Energetic Systems Control

T. Gronier, W. Maréchal, C. Geissler and S. Gibout. MDPI Energies, December 22nd 2022.

Advestis

12 déc. 2022

Partenariat SIMSEO Advestis x CRIANN

Annonce officielle du partenariat SIMSEO entre Advestis et le CRIANN, 12 Décembre 2022.

A Pilot Study on the Use of Generative Adversarial Networks for Data Augmentation of Time Series

Advestis

25 sept. 2022

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.

Advestis

23 sept. 2022

An entry point to clustering methods

W. Maréchal. Medium, September 24th 2022.

Stress testing electrical grids: Generative Adversarial Networks for load scenario generation

Advestis

10 juil. 2022

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).

Relevance of Optimized Low-Scale Green H2 Systems in a French Context: Two Case Studies

Advestis

18 mai 2022

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.

Research

Advestis part of R&D Forvis Mazars has been developing and operating ML algorithms in commercial production since 2013.

Explore our Research below

Clinical Assessment of Puressentiel® Muscles and Joints Gel Aromatherapy in the Management of Osteoarthritis-Related Knee Pain

Integrated sources model: A new space-learning model for heterogeneous multi-view data reduction, visualization, and clustering

Applying non-negative tensor factorization to centered data

Impact of surgical approach on 90-day mortality after lung resection for non-small cell lung cancer in high-risk operable patients

An adaptative approach for estimating the remaining useful life of a heavy-duty fuel cell vehicle

Using Federated Learning for Collaborative Intrusion Detection Systems

On Rank Selection in Non-Negative Matrix Factorization using Concordance

Preventing Acute Limb Ischemia during VA-ECMO—In Silico Analysis of Physical Parameters

Using Federated Learning for collaborative intrusion detection systems

ChatGPT: Usages, impacts & recommandations

Time to market reduction for hydrogen fuel cell stacks using Generative Adversarial Networks

Generative Adversarial Networks applied to synthetic financial scenarios generation

CHAT GPT : USAGES, IMPACTS ET RECOMMANDATIONS

Analysis of the Relevance of Sentiment Data for the Prediction of ERs in a Multi-Asset Framework

Usage of GAMS-Based Digital Twins and Clustering to Improve Energetic Systems Control

Partenariat SIMSEO Advestis x CRIANN

A Pilot Study on the Use of Generative Adversarial Networks for Data Augmentation of Time Series

An entry point to clustering methods

Stress testing electrical grids: Generative Adversarial Networks for load scenario generation

Relevance of Optimized Low-Scale Green H2 Systems in a French Context: Two Case Studies

Advestis part of R&D Forvis Mazars has been developing and operating ML algorithms
in commercial production since 2013.