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cs.LG2026
Generating Financial Time Series by Matching Random Convolutional Features
Konrad J. Mueller, Nikita Zozoulenko, Ben Wood +2
Generating realistic financial time series is challenging as training data is often limited to a single historical path. With such scarce data, overfitting is hard to avoid, especi…
cs.LG2024
Lecture notes on rough paths and applications to machine learning
Thomas Cass, Cristopher Salvi
These notes expound the recent use of the signature transform and rough path theory in data science and machine learning. We develop the core theory of the signature from first pri…