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Found 3 papers, 2 papers with code
Depth-bounded Epistemic Logic
Existing logics typically assume the ability of agents to reason perfectly about propositions of unbounded modal depth.
Transformers à Grande Vitesse
We aim at predicting the travel time of trains on rail sections at the scale of an entire rail network in real-time, by estimating trains' delays relative to a theoretical circulation plan.
Few-shot learning through contextual data augmentation
Machine translation (MT) models used in industries with constantly changing topics, such as translation or news agencies, need to adapt to new data to maintain their performance over time.
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