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Found 4 papers, 2 papers with code
Class-incremental Learning for Time Series: Benchmark and Evaluation
Real-world environments are inherently non-stationary, frequently introducing new classes over time.
Robust Continual Learning through a Comprehensively Progressive Bayesian Neural Network
Thus, as the data for new task streams in, sufficient neurons are added to the network such that the total number of neurons in each layer of the network, including the shared representations with previous tasks and individual task related representation, are equal for all tasks.
Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks
X-ray diffraction (XRD) data acquisition and analysis is among the most time-consuming steps in the development cycle of novel thin-film materials.
Graph Convolutional Neural Networks for Polymers Property Prediction
A fast and accurate predictive tool for polymer properties is demanding and will pave the way to iterative inverse design.
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