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Found 9 papers, 5 papers with code
Time-Adaptive Recurrent Neural Networks
We propose an elegant alternative approach where instead the RNN is in effect resampled in time to match the time of the data.
Towards Lithuanian grammatical error correction
Everyone wants to write beautiful and correct text, yet the lack of language skills, experience, or hasty typing can result in errors.
Correcting diacritics and typos with a ByT5 transformer model
Our approach is also able to restore diacritics in words not seen during training with > 76% accuracy.
Automated age-related macular degeneration area estimation -- first results
This work aims to research an automatic method for detecting Age-related Macular Degeneration (AMD) lesions in RGB eye fundus images.
Generating abstractive summaries of Lithuanian news articles using a transformer model
In this work, we train the first monolingual Lithuanian transformer model on a relatively large corpus of Lithuanian news articles and compare various output decoding algorithms for abstractive news summarization.
Efficient implementations of echo state network cross-validation
The second level of optimization also makes the (ii) part remain constant irrespective of large $k$, as long as the dimension of the output is low.
Localized convolutional neural networks for geospatial wind forecasting
They can be added to any convolutional layers, easily end-to-end trained, introduce minimal additional complexity, and let CNNs retain most of their benefits to the extent that they are needed.
Testing pre-trained Transformer models for Lithuanian news clustering
A recent introduction of Transformer deep learning architecture made breakthroughs in various natural language processing tasks.
Efficient Cross-Validation of Echo State Networks
Thus in many situations $k$-fold cross-validation of ESNs can be done for virtually the same time complexity as a simple single split validation.
