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                <authority type="jury">Jesse Davis</authority>
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                <term xml:lang="en">Commonsense reasoning</term>
                <term xml:lang="en">Knowledge representation and reasoning and learning</term>
                <term xml:lang="en">Representation learning</term>
                <term xml:lang="en">Embedding</term>
                <term xml:lang="fr">Representation des connaissances et raisonnement</term>
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              <p>My habilitation provides a high-level overview of my contributions on inducing commonsense knowledge using vector space representations, with a focus on :  (1)Learning conceptual space representations (learning entity embeddings and region-based representations of concepts, learning interpretable dimensions)(2)  Modelling relational knowledge (relation induction in word embedding and pre-trained language models, learning of distributional relation vectors)(3) Deriving high quality vectors from contextualised LMs and applications to few-shot learning. (4 )Plausible reasoning about ontologies (automated rule base completion, inconsistency handling and belief merging)</p>
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