Get started
Author

Jérémy Roos

Observed names: Jeremy Roos, Jérémy Roos, Roos Jeremy, Roos, Jérémy
ORCID: 0000-0003-2848-8514
Observed ORCID: 0000-0003-2848-8514
OpenAlex ID: A5076239050
A dynamic Bayesian network approach to forecast short-term urban rail passenger flows with incomplete data
2017 · Jérémy Roos, Gérald Gavin, et al. · Transportation research procedia · 79
PDF
Short-Term Urban Rail Passenger Flow Forecasting: A Dynamic Bayesian Network Approach
2016 · Jeremy Roos, Stephane Bonnevay, et al. · International Conference on Machine Learning and Applications · 49
Forecasting passenger flows and headway at train level for a public transport line: Focus on atypical situations
2023 · Thomas Bapaume, Etienne Côme, et al. · Transportation Research Part C Emerging Technologies · 26
Dynamic Bayesian networks with Gaussian mixture models for short-term passenger flow forecasting
2017 · Jeremy Roos, Stephane Bonnevay, et al. · International Conference on Intelligent Systems and Knowledge Engineering (ISKE) · 24
Image Inpainting and Deep Learning to Forecast Short-Term Train Loads
2021 · Thomas Bapaume, Etienne Come, et al. · IEEE Access · 20
PDF
Vision Transformer and Inpainting based Approach for Short-term Forecasting of Passenger Loads on a Transit Metro Line. Focus on Explainability and Atypical Situation prediction
2023 · Bapaume, Thomas, Côme, Etienne, et al. · HAL
PDF
Passenger flow forecasting framework based on vision transformer and inpainting: Application to a public transport system
2022 · Bapaume, Thomas, Come, Etienne, et al. · HAL
Gaussian Mixture Graphical Model Learning and Inference [R package gmgm version 1.0.1]
2020 · Jérémy Roos
gmgm: Gaussian Mixture Graphical Model Learning and Inference
2020 · Jérémy Roos
PDF
Prévision à court terme des flux de voyageurs : une approche par les réseaux bayésiens
2018 · Jérémy Roos · theses.fr (ABES)
PDF
短期都市鉄道旅客流予測:動的Bayesネットワークアプローチ【Powered by NICT】
2016 · Roos Jeremy, Bonnevay Stephane, et al. · IEEE Conference Proceedings
Works count: 11
Citation count: 198
H-index: 5
I10-index: 5
Year
Topic
Type