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Found 5 papers, 2 papers with code
Contextual String Embeddings for Sequence Labeling
Recent advances in language modeling using recurrent neural networks have made it viable to model language as distributions over characters.
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FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP
We present FLAIR, an NLP framework designed to facilitate training and distribution of state-of-the-art sequence labeling, text classification and language models.
Syntax-Aware Language Modeling with Recurrent Neural Networks
Neural language models (LMs) are typically trained using only lexical features, such as surface forms of words.
Regression for sets of polynomial equations
We propose a method called ideal regression for approximating an arbitrary system of polynomial equations by a system of a particular type.
Robust Spatial Filtering with Beta Divergence
The efficiency of Brain-Computer Interfaces (BCI) largely depends upon a reliable extraction of informative features from the high-dimensional EEG signal.
