Sort by
Refine Your Search
-
. This PhD project in Natural Language Processing aims to design generative models capable of automatically simplifying texts into Easy-to-Read and Understand language while preserving their discourse
-
for analyzing how landscapes evolve over time. This thesis is part of the ANR GEvoK (Geographic Entities Evolution in Knowledge Graphs) project, which aims at automatically detecting and semantically
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
expressions, mouthing, spatial organization, and timing. Automatic translation from sign language videos into written text therefore requires modelling complex visual and temporal information, rather than
-
: automating information extraction from unstructured data, proposing a common representation of multi-source data, developing data fusion and knowledge enrichment methods, automatically detecting anomalies, and
-
capable of automatically selecting the simulation strategy best suited to a given prediction objective, while optimizing the trade-off between accuracy and computational cost. The work will build on multi
-
São Paulo, Brazil. The PhD candidate will join LAMIH UMR CNRS 8201, a research laboratory with strong expertise in automatic control, intelligent transportation systems, autonomous and electrified
-
, and to test them experimentally. The next step will be to determine the distribution of deformations required to achieve complex shapes (inverse problem). Finally, we will seek to automatically produce
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
of two main parts: Improve methods for automatically aligning ontologies and linking data by leveraging the scalability, approximation, and multi-viewpoint capabilities of deep learning methods. Study
-
Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
contributions span the entire methodological chain: from automatic dimension reduction via learned summary features [Rodrigues & Gramfort, 2020], to the rigorous statistical calibration of conditional probability