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Found 5 papers, 3 papers with code
DSS: Synthesizing long Digital Ink using Data augmentation, Style encoding and Split generation
As text generative models can give increasingly long answers, we tackle the problem of synthesizing long text in digital ink.
Sampling and Ranking for Digital Ink Generation on a tight computational budget
We use and compare the effect of multiple sampling and ranking techniques, in the first ablation study of its kind in the digital ink domain.
Can we learn gradients by Hamiltonian Neural Networks?
In this work, we propose a meta-learner based on ODE neural networks that learns gradients.
Self-Supervised Neural Architecture Search for Imbalanced Datasets
The results demonstrate how the proposed method can be used in imbalanced datasets, while it can be fully run on a single GPU.
Manifold-based time series forecasting
Prediction for high dimensional time series is a challenging task due to the curse of dimensionality problem.
Denoising
Time Series Forecasting
Statistics Theory
Statistics Theory
