Search Results for author: Duncan Blythe

Found 5 papers, 2 papers with code

FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP

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.

Chunking Named Entity Recognition +2

Contextual String Embeddings for Sequence Labeling

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.

Chunking Language Modelling +3

Syntax-Aware Language Modeling with Recurrent Neural Networks

no code implementations2 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.

Language Modelling

Robust Spatial Filtering with Beta Divergence

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.

EEG

Regression for sets of polynomial equations

no code implementations20 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.

regression

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