Search Results for author:
Found 2 papers, 2 papers with code
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Probabilistic programming languages (PPLs) are receiving widespread attention for performing Bayesian inference in complex generative models.
CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor
Extracting key information from documents, such as receipts or invoices, and preserving the interested texts to structured data is crucial in the document-intensive streamline processes of office automation in areas that includes but not limited to accounting, financial, and taxation areas.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
