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Fatoumata Dama
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2020 – today
- 2024
- [c5]Fatoumata Dama, Rita Sleiman, Steve Bellart:
Introduire l'IA dans la lutte contre la fraude - Comment choisir et convaincre ? APIA 2024: 133-136 - 2023
- [j1]Fatoumata Dama, Christine Sinoquet:
Partially Hidden Markov Chain Multivariate Linear Autoregressive model: inference and forecasting - application to machine health prognostics. Mach. Learn. 112(1): 45-97 (2023) - [c4]Fatoumata Dama, Christine Sinoquet, Corinne Lejus-Bourdeau:
A Framework for Context-Sensitive Prediction in Time Series - Feasibility Study for Data-Driven Simulation in Medicine. DSAA 2023: 1-12 - [c3]Fatoumata Dama, Christine Sinoquet, Corinne Lejus-Bourdeau:
A hidden Markov model with Hawkes process-derived contextual variables to improve time series prediction. Case study in medical simulation. ESANN 2023 - [c2]Jordan Gonzalez, Fatoumata Dama, Laurent Cervoni:
A Novel Incremental Learning Strategy Based on Synthetic Data Generated from a Random Forest. KI 2023: 46-59 - 2021
- [c1]Fatoumata Dama, Christine Sinoquet:
Prediction and Inference in a Partially Hidden Markov-switching Framework with Autoregression. Application to Machinery Health Diagnosis. ICTAI 2021: 1-9 - [i2]Fatoumata Dama, Christine Sinoquet:
Partially Hidden Markov Chain Linear Autoregressive model: inference and forecasting. CoRR abs/2102.12584 (2021) - [i1]Fatoumata Dama, Christine Sinoquet:
Analysis and modeling to forecast in time series: a systematic review. CoRR abs/2104.00164 (2021)
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last updated on 2024-09-21 02:37 CEST by the dblp team
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