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Found 3 papers, 2 papers with code
PCF-GAN: generating sequential data via the characteristic function of measures on the path space
Generating high-fidelity time series data using generative adversarial networks (GANs) remains a challenging task, as it is difficult to capture the temporal dependence of joint probability distributions induced by time-series data.
Beating the Best: Improving on AlphaFold2 at Protein Structure Prediction
We developed the ARStack PSP method by stacking AlphaFold2 and RoseTTAFold.
Path Development Network with Finite-dimensional Lie Group Representation
To tackle this problem, we propose a novel, trainable path development layer, which exploits representations of sequential data with the help of finite-dimensional matrix Lie groups.
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