jwyyy/AdaFNN
[ICML 2021] Deep Learning for Functional Data Analysis with Adaptive Basis Layers
This project offers a deep learning model for analyzing functional data, which are measurements that vary continuously over an interval, like a curve or a waveform. It takes in these continuous data observations and helps identify underlying patterns or make predictions, which is useful for researchers and data scientists working with complex time-series or spatially varying information.
No commits in the last 6 months.
Use this if you need to apply deep learning techniques to functional data, where each data point is a curve, function, or other continuous observation, rather than a single discrete value.
Not ideal if your data consists of discrete, scalar measurements rather than continuous functions or curves.
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Last pushed
Sep 27, 2022
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