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cs.LG2026
CAARL: In-Context Learning for Interpretable Co-Evolving Time Series Forecasting
Etienne Tajeuna, Patrick Asante Owusu, Armelle Brun +1
In this paper we investigate forecasting coevolving time series that feature intricate dependencies and nonstationary dynamics by using an LLM Large Language Models approach We pro…
cs.LG2025
GRAVITY: A Controversial Graph Representation Learning for Vertex Classification
Etienne Gael Tajeuna, Jean Marie Tshimula
In the quest of accurate vertex classification, we introduce GRAVITY (Graph-based Representation leArning via Vertices Interaction TopologY), a framework inspired by physical syste…
cs.LG2024
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions
René Manassé Galekwa, Jean Marie Tshimula, Etienne Gael Tajeuna +1
The sports betting industry has experienced rapid growth, driven largely by technological advancements and the proliferation of online platforms. Machine learning (ML) has played a…