1 code implementation • NAACL 2019 • Alan Akbik, Tanja Bergmann, Duncan Blythe, Kashif Rasul, Stefan Schweter, Rol Vollgraf,
We present FLAIR, an NLP framework designed to facilitate training and distribution of state-of-the-art sequence labeling, text classification and language models.
1 code implementation • COLING 2018 • Alan Akbik, Duncan Blythe, Rol Vollgraf,
Recent advances in language modeling using recurrent neural networks have made it viable to model language as distributions over characters.
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no code implementations • 2 Mar 2018 • Duncan Blythe, Alan Akbik, Roland Vollgraf
Neural language models (LMs) are typically trained using only lexical features, such as surface forms of words.
no code implementations • NeurIPS 2013 • Wojciech Samek, Duncan Blythe, Klaus-Robert Müller, Motoaki Kawanabe
The efficiency of Brain-Computer Interfaces (BCI) largely depends upon a reliable extraction of informative features from the high-dimensional EEG signal.
no code implementations • 20 Oct 2011 • Franz Johannes Király, Paul von Bünau, Jan Saputra Müller, Duncan Blythe, Frank Meinecke, Klaus-Robert Müller
We propose a method called ideal regression for approximating an arbitrary system of polynomial equations by a system of a particular type.