Raphael Fournier-S'niehotta — accepted AI-conference papers

2024

Supra-Laplacian Encoding for Transformer on Dynamic Graphs

Yannis Karmim, Marc Lafon, Raphael Fournier-S'niehotta, Nicolas THOME

NeurIPS 2024poster

Fully connected Graph Transformers (GT) have rapidly become prominent in the static graph community as an alternative to Message-Passing models, which suffer from a lack of expressivity, oversquashing, and under-reaching. However, in a dynamic context, by interconnecting all nodes at multiple snapsh…

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2023

NeoMaPy: A Framework for Computing MAP Inference on Temporal Knowledge Graphs

Victor David, Raphael Fournier-S'niehotta, Nicolas Travers

IJCAI 2023poster

Markov Logic Networks (MLN) are used for reasoning on uncertain and inconsistent temporal data. We proposed the TMLN (Temporal Markov Logic Network) which extends them with sorts/types, weights on rules and facts, and various temporal consistencies. The NeoMaPy framework integrates it as a knowledge…

Cited by 2 Source ↗PDF ↗code ↗Scholar ↗